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Outputs (147)

A transformer-based approach empowered by a self-attention technique for semantic segmentation in remote sensing (2024)
Journal Article
Boulila, W., Ghandorh, H., Masood, S., Alzahem, A., Koubaa, A., Ahmed, F., Khan, Z., & Ahmad, J. (2024). A transformer-based approach empowered by a self-attention technique for semantic segmentation in remote sensing. Heliyon, 10(8), Article e29396. http

Semantic segmentation of Remote Sensing (RS) images involves the classification of each pixel in a satellite image into distinct and non-overlapping regions or segments. This task is crucial in various domains, including land cover classification, au... Read More about A transformer-based approach empowered by a self-attention technique for semantic segmentation in remote sensing.

A Self-Attention-Based Deep Convolutional Neural Networks for IIoT Networks Intrusion Detection (2024)
Journal Article
Alshehri, M. S., Saidani, O., Alrayes, F. S., Abbasi, S. F., & Ahmad, J. (2024). A Self-Attention-Based Deep Convolutional Neural Networks for IIoT Networks Intrusion Detection. IEEE Access, 12, 45762-45772. https://doi.org/10.1109/access.2024.3380816

The Industrial Internet of Things (IIoT) comprises a variety of systems, smart devices, and an extensive range of communication protocols. Hence, these systems face susceptibility to privacy and security challenges, making them prime targets for mali... Read More about A Self-Attention-Based Deep Convolutional Neural Networks for IIoT Networks Intrusion Detection.

SkipGateNet: A Lightweight CNN-LSTM Hybrid Model with Learnable Skip Connections for Efficient Botnet Attack Detection in IoT (2024)
Journal Article
Alshehri, M. S., Ahmad, J., Almakdi, S., Qathrady, M. A., Ghadi, Y. Y., & Buchanan, W. J. (2024). SkipGateNet: A Lightweight CNN-LSTM Hybrid Model with Learnable Skip Connections for Efficient Botnet Attack Detection in IoT. IEEE Access, 12, https://doi.o

The rise of Internet of Things (IoT) has led to increased security risks, particularly from botnet attacks that exploit IoT device vulnerabilities. This situation necessitates effective Intrusion Detection Systems (IDS), that are accurate, lightweigh... Read More about SkipGateNet: A Lightweight CNN-LSTM Hybrid Model with Learnable Skip Connections for Efficient Botnet Attack Detection in IoT.

ASB-CS: Adaptive sparse basis compressive sensing model and its application to medical image encryption (2024)
Journal Article
Jiang, D., Tsafack, N., Boulila, W., Ahmad, J., & Barba-Franco, J. (in press). ASB-CS: Adaptive sparse basis compressive sensing model and its application to medical image encryption. Expert Systems with Applications, 236, Article 121378. https://doi.org/

Recent advances in intelligent wearable devices have brought tremendous chances for the development of healthcare monitoring system. However, the data collected by various sensors in it are user-privacy-related information. Once the individuals’ priv... Read More about ASB-CS: Adaptive sparse basis compressive sensing model and its application to medical image encryption.

Decision Making and Security Risk Management for IoT Environments (2024)
Book
Boulila, W., Ahmad, J., Koubaa, A., Driss, M., & Farah, I. R. (Eds.). (2024). Decision Making and Security Risk Management for IoT Environments. Springer. https://doi.org/10.1007/978-3-031-47590-0

This book contains contemporary research that outlines and addresses security, privacy challenges and decision-making in IoT environments. The authors provide a variety of subjects related to the following Keywords: IoT, security, AI, deep learning,... Read More about Decision Making and Security Risk Management for IoT Environments.

British Sign Language Detection Using Ultra-Wideband Radar Sensing and Residual Neural Network (2024)
Journal Article
Saeed, U., Shah, S. A., Ghadi, Y. Y., Hameed, H., Shah, S. I., Ahmad, J., & Abbasi, Q. H. (2024). British Sign Language Detection Using Ultra-Wideband Radar Sensing and Residual Neural Network. IEEE Sensors Journal, 24(7), 11144-11151. https://doi.org/10.

This study represents a significant advancement in Sign Language Detection (SLD), a crucial tool for enhancing communication and fostering inclusivity among the hearing-impaired community. It innovatively combines radar technology with deep learning... Read More about British Sign Language Detection Using Ultra-Wideband Radar Sensing and Residual Neural Network.

A novel medical image data protection scheme for smart healthcare system (2024)
Journal Article
Rehman, M. U., Shafique, A., Khan, M. S., Driss, M., Boulila, W., Ghadi, Y. Y., …Ahmad, J. (in press). A novel medical image data protection scheme for smart healthcare system. CAAI Transactions on Intelligence Technology, https://doi.org/10.1049/cit2.1

The Internet of Multimedia Things (IoMT) refers to a network of interconnected multimedia devices that communicate with each other over the Internet. Recently, smart healthcare has emerged as a significant application of the IoMT, particularly in the... Read More about A novel medical image data protection scheme for smart healthcare system.

Energy efficiency considerations in software‐defined wireless body area networks (2024)
Journal Article
Masood, F., Khan, W. U., Alshehri, M. S., Alsumayt, A., & Ahmad, J. (2024). Energy efficiency considerations in software‐defined wireless body area networks. Engineering Reports, 6(3), Article e12841. https://doi.org/10.1002/eng2.12841

Wireless body area networks (WBAN) provide remote services for patient monitoring which allows healthcare practitioners to diagnose, monitor, and prescribe them without their physical presence. To address the shortcomings of WBAN, software-defined ne... Read More about Energy efficiency considerations in software‐defined wireless body area networks.

Multi-modal Features Representation-based Convolutional Neural Network Model for Malicious Website Detection (2023)
Journal Article
Alsaedi, M., Ghaleb, F. A., Saeed, F., Ahmad, J., & Alasli, M. (2024). Multi-modal Features Representation-based Convolutional Neural Network Model for Malicious Website Detection. IEEE Access, 12, 7271 - 7284. https://doi.org/10.1109/access.2023.3348071

Web applications have proliferated across various business sectors, serving as essential tools for billions of users in their daily lives activities. However, many of these applications are malicious which is a major threat to Internet users as they... Read More about Multi-modal Features Representation-based Convolutional Neural Network Model for Malicious Website Detection.

Sustainable Collaboration: Federated Learning for Environmentally Conscious Forest Fire Classification in Green Internet of Things (IoT) (2023)
Journal Article
Siddique, A. A., Alasbali, N., Driss, M., Boulila, W., Alshehri, M. S., & Ahmad, J. (2024). Sustainable Collaboration: Federated Learning for Environmentally Conscious Forest Fire Classification in Green Internet of Things (IoT). Internet of Things, 25, A

Forests are an invaluable natural resource, playing a crucial role in the regulation of both local and global climate patterns. Additionally, they offer a plethora of benefits such as medicinal plants, food, and non-timber forest products. However, w... Read More about Sustainable Collaboration: Federated Learning for Environmentally Conscious Forest Fire Classification in Green Internet of Things (IoT).

DTL-IDS: An optimized Intrusion Detection Framework using Deep Transfer Learning and Genetic Algorithm (2023)
Journal Article
Latif, S., Boulila, W., Koubaa, A., Zou, Z., & Ahmad, J. (2024). DTL-IDS: An optimized Intrusion Detection Framework using Deep Transfer Learning and Genetic Algorithm. Journal of Network and Computer Applications, 221, 103784. https://doi.org/10.1016/j.j

In the dynamic field of the Industrial Internet of Things (IIoT), the networks are increasingly vulnerable to a diverse range of cyberattacks. This vulnerability necessitates the development of advanced intrusion detection systems (IDSs). Addressing... Read More about DTL-IDS: An optimized Intrusion Detection Framework using Deep Transfer Learning and Genetic Algorithm.

A novel routing optimization strategy based on reinforcement learning in perception layer networks (2023)
Journal Article
Tan, H., Ye, T., ur Rehman, S., ur Rehman, O., Tu, S., & Ahmad, J. (2023). A novel routing optimization strategy based on reinforcement learning in perception layer networks. Computer Networks, 237, Article 110105. https://doi.org/10.1016/j.comnet.2023.11

Wireless sensor networks have become incredibly popular due to the Internet of Things’ (IoT) rapid development. IoT routing is the basis for the efficient operation of the perception-layer network. As a popular type of machine learning, reinforcement... Read More about A novel routing optimization strategy based on reinforcement learning in perception layer networks.

Automatic neonatal sleep stage classification: A comparative study (2023)
Journal Article
Abbasi, S. F., Abbas, A., Ahmad, I., Alshehri, M. S., Almakdi, S., Ghadi, Y. Y., & Ahmad, J. (2023). Automatic neonatal sleep stage classification: A comparative study. Heliyon, 9(11), Article e22195. https://doi.org/10.1016/j.heliyon.2023.e22195

Sleep is an essential feature of living beings. For neonates, it is vital for their mental and physical development. Sleep stage cycling is an important parameter to assess neonatal brain and physical development. Therefore, it is crucial to administ... Read More about Automatic neonatal sleep stage classification: A comparative study.

TNN-IDS: Transformer neural network-based intrusion detection system for MQTT-enabled IoT Networks (2023)
Journal Article
Ullah, S., Ahmad, J., Khan, M. A., Alshehri, M. S., Boulila, W., Koubaa, A., …Iqbal Ch, M. M. (2023). TNN-IDS: Transformer neural network-based intrusion detection system for MQTT-enabled IoT Networks. Computer Networks, 237, Article 110072. https://doi

The Internet of Things (IoT) is a global network that connects a large number of smart devices. MQTT is a de facto standard, lightweight, and reliable protocol for machine-to-machine communication, widely adopted in IoT networks. Various smart device... Read More about TNN-IDS: Transformer neural network-based intrusion detection system for MQTT-enabled IoT Networks.

MAGRU-IDS: A Multi-Head Attention-based Gated Recurrent Unit for Intrusion Detection in IIoT Networks (2023)
Journal Article
Ullah, S., Boulila, W., Koubaa, A., & Ahmad, J. (2023). MAGRU-IDS: A Multi-Head Attention-based Gated Recurrent Unit for Intrusion Detection in IIoT Networks. IEEE Access, 11, 114590-114601. https://doi.org/10.1109/access.2023.3324657

The increasing prevalence of the Industrial Internet of Things (IIoT) in industrial environments amplifies the potential for security breaches and compromises. To monitor IIoT networks, intrusion detection systems (IDS) have been introduced to detect... Read More about MAGRU-IDS: A Multi-Head Attention-based Gated Recurrent Unit for Intrusion Detection in IIoT Networks.

Intrusion Detection Systems Using Machine Learning (2023)
Book Chapter
Taylor, W., Hussain, A., Gogate, M., Dashtipour, K., & Ahmad, J. (2024). Intrusion Detection Systems Using Machine Learning. In W. Boulila, J. Ahmad, A. Koubaa, M. Driss, & I. Riadh Farah (Eds.), Decision Making and Security Risk Management for IoT Enviro

Intrusion detection systems (IDS) have developed and evolved over time to form an important component in network security. The aim of an intrusion detection system is to successfully detect intrusions within a network and to trigger alerts to system... Read More about Intrusion Detection Systems Using Machine Learning.

AI-Enabled Traffic Control Prioritization in Software-Defined IoT Networks for Smart Agriculture (2023)
Journal Article
Masood, F., Khan, W. U., Jan, S. U., & Ahmad, J. (2023). AI-Enabled Traffic Control Prioritization in Software-Defined IoT Networks for Smart Agriculture. Sensors, 23(19), Article 8218. https://doi.org/10.3390/s23198218

Smart agricultural systems have received a great deal of interest in recent years because of their potential for improving the efficiency and productivity of farming practices. These systems gather and analyze environmental data such as temperature,... Read More about AI-Enabled Traffic Control Prioritization in Software-Defined IoT Networks for Smart Agriculture.

Privacy-Enhanced Pneumonia Diagnosis: IoT-Enabled Federated Multi-Party Computation in Industry 5.0 (2023)
Journal Article
Siddique, A. A., Boulila, W., Alshehri, M. S., Ahmed, F., Gadekallu, T. R., Victor, N., …Ahmad, J. (2023). Privacy-Enhanced Pneumonia Diagnosis: IoT-Enabled Federated Multi-Party Computation in Industry 5.0. IEEE Transactions on Consumer Electronics, ht

Pneumonia is a significant global health concern that can lead to severe and sometimes fatal consequences. Timely identification and classification of pneumonia can substantially improve patient outcomes. However, the disclosure of sensitive medical... Read More about Privacy-Enhanced Pneumonia Diagnosis: IoT-Enabled Federated Multi-Party Computation in Industry 5.0.

FireXnet: an explainable AI-based tailored deep learning model for wildfire detection on resource-constrained devices (2023)
Journal Article
Ahmad, K., Khan, M. S., Ahmed, F., Driss, M., Boulila, W., Alazeb, A., …Ahmad, J. (2023). FireXnet: an explainable AI-based tailored deep learning model for wildfire detection on resource-constrained devices. Fire Ecology, 19, Article 54. https://doi.or

Background: Forests cover nearly one-third of the Earth’s land and are some of our most biodiverse ecosystems. Due to climate change, these essential habitats are endangered by increasing wildfires. Wildfires are not just a risk to the environment, b... Read More about FireXnet: an explainable AI-based tailored deep learning model for wildfire detection on resource-constrained devices.

Enhancing IoT network security through deep learning-powered Intrusion Detection System (2023)
Journal Article
Bakhsh, S. A., Khan, M. A., Ahmed, F., Alshehri, M. S., Ali, H., & Ahmad, J. (2023). Enhancing IoT network security through deep learning-powered Intrusion Detection System. Internet of Things, 24, Article 100936. https://doi.org/10.1016/j.iot.2023.100936

The rapid growth of the Internet of Things (IoT) has brought about a global concern for the security of interconnected devices and networks. This necessitates the use of efficient Intrusion Detection System (IDS) to mitigate cyber threats. Deep learn... Read More about Enhancing IoT network security through deep learning-powered Intrusion Detection System.

Extracting Visual Micro-Doppler Signatures from Human Lips Motion Using UoG Radar Sensing Data for Hearing Aid Applications (2023)
Journal Article
Saeed, U., Shah, S. A., Ghadi, Y. Y., Khan, M. Z., Ahmad, J., Shah, S. I., …Abbasi, Q. H. (2023). Extracting Visual Micro-Doppler Signatures from Human Lips Motion Using UoG Radar Sensing Data for Hearing Aid Applications. IEEE Sensors Journal, 23(19),

This study proposes a secure and effective lips-reading system that can accurately detect lips movements, even when face masks are worn. The system utilizes radio frequency (RF) sensing and ultra-wideband (UWB) radar technology, which overcomes the c... Read More about Extracting Visual Micro-Doppler Signatures from Human Lips Motion Using UoG Radar Sensing Data for Hearing Aid Applications.

SRSS: A New Chaos-Based Single-Round Single S-Box Image Encryption Scheme for Highly Auto-Correlated Data (2023)
Presentation / Conference Contribution
Shahbaz Khan, M., Ahmad, J., Ali, H., Pitropakis, N., Al-Dubai, A., Ghaleb, B., & Buchanan, W. J. (2023, October). SRSS: A New Chaos-Based Single-Round Single S-Box Image Encryption Scheme for Highly Auto-Correlated Data. Presented at 9th International Co

With the advent of digital communication, securing digital images during transmission and storage has become a critical concern. The traditional s-box substitution methods often fail to effectively conceal the information within highly auto-correlate... Read More about SRSS: A New Chaos-Based Single-Round Single S-Box Image Encryption Scheme for Highly Auto-Correlated Data.

A Comparison of Ensemble Learning for Intrusion Detection in Telemetry Data (2023)
Presentation / Conference Contribution
Naz, N., Khan, M. A., Khan, M. A., Khan, M. A., Jan, S. U., Shah, S. A., …Ahmad, J. (2023). A Comparison of Ensemble Learning for Intrusion Detection in Telemetry Data. In Advances on Intelligent Computing and Data Science. ICACIn 2022 (451-462). https

The Internet of Things (IoT) is a grid of interconnected pre-programmed electronic devices to provide intelligent services for daily life tasks. However, the security of such networks is a considerable obstacle to successful implementation. Therefore... Read More about A Comparison of Ensemble Learning for Intrusion Detection in Telemetry Data.

An efficient deep learning model for brain tumour detection with privacy preservation (2023)
Journal Article
Rehman, M. U., Shafique, A., Khan, I. U., Ghadi, Y. Y., Ahmad, J., Alshehri, M. S., …Zayyan, M. H. (in press). An efficient deep learning model for brain tumour detection with privacy preservation. CAAI Transactions on Intelligence Technology, https://d

Internet of medical things (IoMT) is becoming more prevalent in healthcare applications as a result of current AI advancements, helping to improve our quality of life and ensure a sustainable health system. IoMT systems with cutting‐edge scientific c... Read More about An efficient deep learning model for brain tumour detection with privacy preservation.

A Hybrid Deep Learning-based Intrusion Detection System for IoT Networks (2023)
Journal Article
Khan, N. W., Alshehri, M. S., Khan, M. A., Almakdi, S., Moradpoor, N., Alazeb, A., …Ahmad, J. (2023). A Hybrid Deep Learning-based Intrusion Detection System for IoT Networks. Mathematical Biosciences and Engineering, 20(8), 13491-13520. https://doi.org

The Internet of Things (IoT) is a rapidly evolving technology with a wide range of potential applications, but the security of IoT networks remains a major concern. The existing system needs improvement in detecting intrusions in IoT networks. Severa... Read More about A Hybrid Deep Learning-based Intrusion Detection System for IoT Networks.

Prediction of the SARS-CoV-2 Derived T-Cell Epitopes’ Response Against COVID Variants (2023)
Journal Article
Tahir, H., Shahbaz Khan, M., Ahmed, F., M. Albarrak, A., Noman Qasem, S., & Ahmad, J. (2023). Prediction of the SARS-CoV-2 Derived T-Cell Epitopes’ Response Against COVID Variants. Computers, Materials & Continua, 75(2), 3517-3535. https://doi.org/10.32

The COVID-19 outbreak began in December 2019 and was declared a global health emergency by the World Health Organization. The four most dominating variants are Beta, Gamma, Delta, and Omicron. After the administration of vaccine doses, an eminent dec... Read More about Prediction of the SARS-CoV-2 Derived T-Cell Epitopes’ Response Against COVID Variants.

A DNA Based Colour Image Encryption Scheme Using A Convolutional Autoencoder (2023)
Journal Article
Ahmed, F., Rehman, M. U., Ahmad, J., Khan, M. S., Boulila, W., Srivastava, G., …Buchanan, W. J. (2023). A DNA Based Colour Image Encryption Scheme Using A Convolutional Autoencoder. ACM transactions on multimedia computing communications and application

With the advancement in technology, digital images can easily be transmitted and stored over the Internet. Encryption is used to avoid illegal interception of digital images. Encrypting large-sized colour images in their original dimension generally... Read More about A DNA Based Colour Image Encryption Scheme Using A Convolutional Autoencoder.

The Mobile Attacks Under Internet of Things Networks (2023)
Presentation / Conference Contribution
Kean, C., Ghaleb, B., Mcclelland, B., Ahmad, J., Wadhaj, I., & Thomson, C. (2023). The Mobile Attacks Under Internet of Things Networks. In Proceedings of the 2nd International Conference on Emerging Technologies and Intelligent Systems ICETIS 2022: Volu

Since the introduction of the Routing Protocol for Low Power and Lossy Networks (RPL), its security aspects have been the focus of the scientific community who reported several security flaws that left the protocol vulnerable for several attacks. In... Read More about The Mobile Attacks Under Internet of Things Networks.

An Efficient Optimization of Battery-Drone-Based Transportation Systems for Monitoring Solar Power Plant (2022)
Journal Article
Jemmali, M., Bashir, A. K., Boulila, W., Melhim, L. K. B., Jhaveri, R. H., & Ahmad, J. (2023). An Efficient Optimization of Battery-Drone-Based Transportation Systems for Monitoring Solar Power Plant. IEEE Transactions on Intelligent Transportation System

Nowadays, developing environmental solutions to ensure the preservation and sustainability of natural resources is one of the core research topics for providing a better life quality. Using renewable energy sources, such as solar energy, is one of th... Read More about An Efficient Optimization of Battery-Drone-Based Transportation Systems for Monitoring Solar Power Plant.

Forensic Analysis of Blackhole Attack in Wireless Sensor Networks/Internet of Things (2022)
Journal Article
Hasan, A., Khan, M. A., Shabir, B., Munir, A., Malik, A. W., Anwar, Z., & Ahmad, J. (2022). Forensic Analysis of Blackhole Attack in Wireless Sensor Networks/Internet of Things. Applied Sciences, 12(22), Article 11442. https://doi.org/10.3390/app122211442

The internet of things (IoT) is prone to various types of denial of service (DoS) attacks due to their resource-constrained nature. Extensive research efforts have been dedicated to securing these systems, but various vulnerabilities remain. Notably,... Read More about Forensic Analysis of Blackhole Attack in Wireless Sensor Networks/Internet of Things.

Multi-Chaos-Based Lightweight Image Encryption-Compression for Secure Occupancy Monitoring (2022)
Journal Article
Ghadi, Y. Y., Alsuhibany, S. A., Ahmad, J., Kumar, H., Boulila, W., Alsaedi, M., …Bhatti, S. A. (2022). Multi-Chaos-Based Lightweight Image Encryption-Compression for Secure Occupancy Monitoring. Journal of Healthcare Engineering, 2022, Article 7745132.

With the advancement of camera and wireless technologies, surveillance camera-based occupancy has received ample attention from the research community. However, camera-based occupancy monitoring and wireless channels, especially Wi-Fi hotspot, pose s... Read More about Multi-Chaos-Based Lightweight Image Encryption-Compression for Secure Occupancy Monitoring.

A Proposal of a New Chaotic Map for Application in the Image Encryption Domain (2022)
Journal Article
Abu-Amara, F., & Ahmad, J. (2023). A Proposal of a New Chaotic Map for Application in the Image Encryption Domain. Journal of Information and Knowledge Management, 22(2), Article 2250088. https://doi.org/10.1142/s0219649222500885

Several chaos-based image encryption schemes have been proposed in the last decade. Each encryption scheme has pros and cons regarding its speed, complexity, and security. This paper proposes a new chaotic map called Power-Chaotic Map (PCM). Characte... Read More about A Proposal of a New Chaotic Map for Application in the Image Encryption Domain.

The Development of a Cross-Border Energy Trade Cooperation Model of Interconnected Virtual Power Plants Using Bilateral Contracts (2022)
Journal Article
Ullah, Z., Arshad, & Ahmad, J. (2022). The Development of a Cross-Border Energy Trade Cooperation Model of Interconnected Virtual Power Plants Using Bilateral Contracts. Energies, 15(21), Article 8171. https://doi.org/10.3390/en15218171

By coordinating the operation of regionally interconnected virtual power plants (VPPs), the growing penetration problem of renewable energy sources (RESs) into the power system can be addressed. This study presents an interactive trading cooperation... Read More about The Development of a Cross-Border Energy Trade Cooperation Model of Interconnected Virtual Power Plants Using Bilateral Contracts.

An Efficient Lightweight Image Encryption Scheme Using Multichaos (2022)
Journal Article
Ullah, A., Shah, A. A., Khan, J. S., Sajjad, M., Boulila, W., Akgul, A., …Ahmad, J. (2022). An Efficient Lightweight Image Encryption Scheme Using Multichaos. Security and Communication Networks, 2022, Article 5680357. https://doi.org/10.1155/2022/56803

With an immense increase in Internet multimedia applications over the past few years, digital content such as digital images are stored and shared over global networks, the probability for information leakage and illegal modifications to the digital... Read More about An Efficient Lightweight Image Encryption Scheme Using Multichaos.

Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform (2022)
Journal Article
Ali, H., Ahmad, J., Jaroucheh, Z., Papadopoulos, P., Pitropakis, N., Lo, O., …Buchanan, W. J. (2022). Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform. Entropy, 24(10), Article 1379. ht

Historically, threat information sharing has relied on manual modelling and centralised network systems, which can be inefficient, insecure, and prone to errors. Alternatively, private blockchains are now widely used to address these issues and impro... Read More about Trusted Threat Intelligence Sharing in Practice and Performance Benchmarking through the Hyperledger Fabric Platform.

A Lightweight Image Encryption Algorithm Based on Chaotic Map and Random Substitution (2022)
Journal Article
Alghamdi, Y., Munir, A., & Ahmad, J. (2022). A Lightweight Image Encryption Algorithm Based on Chaotic Map and Random Substitution. Entropy, 24(10), Article 1344. https://doi.org/10.3390/e24101344

Chaotic-maps-based image encryption methods have been a topic of research interest for a decade. However, most of the proposed methods suffer from slow encryption time or compromise on the security of the encryption to achieve faster encryption. This... Read More about A Lightweight Image Encryption Algorithm Based on Chaotic Map and Random Substitution.

Classification of Skin Cancer Lesions Using Explainable Deep Learning (2022)
Journal Article
Zia Ur Rehman, M., Ahmed, F., Alsuhibany, S. A., Jamal, S. S., Zulfiqar Ali, M., & Ahmad, J. (2022). Classification of Skin Cancer Lesions Using Explainable Deep Learning. Sensors, 22(18), Article 6915. https://doi.org/10.3390/s22186915

Skin cancer is among the most prevalent and life-threatening forms of cancer that occur worldwide. Traditional methods of skin cancer detection need an in-depth physical examination by a medical professional, which is time-consuming in some cases. Re... Read More about Classification of Skin Cancer Lesions Using Explainable Deep Learning.

A Novel Chaos-Based Privacy-Preserving Deep Learning Model for Cancer Diagnosis (2022)
Journal Article
Rehman, M. U., Shafique, A., Ghadi, Y. Y., Boulila, W., Jan, S. U., Gadekallu, T. R., …Ahmad, J. (2022). A Novel Chaos-Based Privacy-Preserving Deep Learning Model for Cancer Diagnosis. IEEE Transactions on Network Science and Engineering, 9(6), 4322-43

Early cancer identification is regarded as a challenging problem in cancer prevention for the healthcare community. In addition, ensuring privacy-preserving healthcare data becomes more difficult with the growing demand for sharing these data. This s... Read More about A Novel Chaos-Based Privacy-Preserving Deep Learning Model for Cancer Diagnosis.

Predicting Breast Cancer Leveraging Supervised Machine Learning Techniques (2022)
Journal Article
Aamir, S., Rahim, A., Aamir, Z., Abbasi, S. F., Khan, M. S., Alhaisoni, M., …Ahmad, J. (2022). Predicting Breast Cancer Leveraging Supervised Machine Learning Techniques. Computational and Mathematical Methods in Medicine, 2022, Article 5869529. https:/

Breast cancer is one of the leading causes of increasing deaths in women worldwide. The complex nature (microcalcification and masses) of breast cancer cells makes it quite difficult for radiologists to diagnose it properly. Subsequently, various com... Read More about Predicting Breast Cancer Leveraging Supervised Machine Learning Techniques.

Machine Learning-Based Prediction of Node Localization Accuracy in IIoT-Based MI-UWSNs and Design of a TD Coil for Omnidirectional Communication (2022)
Journal Article
Gang, Q., Muhammad, A., Khan, Z. U., Khan, M. S., Ahmed, F., & Ahmad, J. (2022). Machine Learning-Based Prediction of Node Localization Accuracy in IIoT-Based MI-UWSNs and Design of a TD Coil for Omnidirectional Communication. Sustainability, 14(15), Arti

This study aims to realize Sustainable Development Goals (SDGs), i.e., SDG 9: Industry Innovation and Infrastructure and SDG 14: Life below Water, through the improvement of localization estimation accuracy in magneto-inductive underwater wireless se... Read More about Machine Learning-Based Prediction of Node Localization Accuracy in IIoT-Based MI-UWSNs and Design of a TD Coil for Omnidirectional Communication.

Automated Grading of Diabetic Macular Edema Using Color Retinal Photographs (2022)
Presentation / Conference Contribution
Zubair, M., Ahmad, J., Alqahtani, F., Khan, F., Shah, S. A., Abbasi, Q. H., & Jan, S. U. (2022). Automated Grading of Diabetic Macular Edema Using Color Retinal Photographs. In 2022 2nd International Conference of Smart Systems and Emerging Technologies

Diabetic Macular Edema (DME) is an advanced indication of diabetic retinopathy (DR). It starts with blurring in vision and can lead to partial or even complete irreversible visual compromise. The only cure is timely diagnosis, prevention and treatmen... Read More about Automated Grading of Diabetic Macular Edema Using Color Retinal Photographs.

DRaNN_PSO: A deep random neural network with particle swarm optimization for intrusion detection in the industrial internet of things (2022)
Journal Article
Ahmad, J., Shah, S. A., Latif, S., Ahmed, F., Zou, Z., & Pitropakis, N. (2022). DRaNN_PSO: A deep random neural network with particle swarm optimization for intrusion detection in the industrial internet of things. Journal of King Saud University (Compute

The Industrial Internet of Things (IIoT) is a rapidly emerging technology that increases the efficiency and productivity of industrial environments by integrating smart sensors and devices with the internet. The advancements in communication technolo... Read More about DRaNN_PSO: A deep random neural network with particle swarm optimization for intrusion detection in the industrial internet of things.

A novel security and authentication method for infrared medical image with discrete time chaotic systems (2022)
Journal Article
Boyraz, O. F., Guleryuz, E., Akgul, A., Yildiz, M. Z., Kiran, H. E., & Ahmad, J. (2022). A novel security and authentication method for infrared medical image with discrete time chaotic systems. Optik, 267, Article 169717. https://doi.org/10.1016/j.ijleo.

Objective: Hand vein images have become important biometric signs used for identification systems. Also, dorsal hand vein images have noteworthy advantages in terms of reliability and contactless procedure. Surgically changing the vascular pattern u... Read More about A novel security and authentication method for infrared medical image with discrete time chaotic systems.

Ensemble learning-based IDS for sensors telemetry data in IoT networks (2022)
Journal Article
Naz, N., Khan, M. A., Alsuhibany, S. A., Diyan, M., Tan, Z., Khan, M. A., & Ahmad, J. (2022). Ensemble learning-based IDS for sensors telemetry data in IoT networks. Mathematical Biosciences and Engineering, 19(10), 10550-10580. https://doi.org/10.3934/mb

The Internet of Things (IoT) is a paradigm that connects a range of physical smart devices to provide ubiquitous services to individuals and automate their daily tasks. IoT devices collect data from the surrounding environment and communicate with ot... Read More about Ensemble learning-based IDS for sensors telemetry data in IoT networks.

A Deep Learning-Based Semantic Segmentation Architecture for Autonomous Driving Applications (2022)
Journal Article
Masood, S., Ahmed, F., Alsuhibany, S. A., Ghadi, Y. Y., Siyal, M. Y., Kumar, H., …Ahmad, J. (2022). A Deep Learning-Based Semantic Segmentation Architecture for Autonomous Driving Applications. Wireless Communications and Mobile Computing, 2022, Article

In recent years, the development of smart transportation has accelerated research on semantic segmentation as it is one of the most important problems in this area. A large receptive field has always been the center of focus when designing convolutio... Read More about A Deep Learning-Based Semantic Segmentation Architecture for Autonomous Driving Applications.

Modified SHARK Cipher and Duffing Map-Based Cryptosystem (2022)
Journal Article
Rabie, O., Ahmad, J., & Alghazzawi, D. (2022). Modified SHARK Cipher and Duffing Map-Based Cryptosystem. Mathematics, 10(12), Article 2034. https://doi.org/10.3390/math10122034

Recent years have seen a lot of interest in the study of chaotic structures and their accompanying cryptography frameworks. In this research, we came up with a new way to encrypt images that used the chaos and a modified block cipher named the SHARK... Read More about Modified SHARK Cipher and Duffing Map-Based Cryptosystem.

A Secure and Lightweight Chaos Based Image Encryption Scheme (2022)
Journal Article
Ali Khan, F., Ahmed, J., Alqahtani, F., Alsuhibany, S. A., Ahmed, F., & Ahmad, J. (2022). A Secure and Lightweight Chaos Based Image Encryption Scheme. Computers, Materials & Continua, 73(1), 279-294. https://doi.org/10.32604/cmc.2022.028789

In this paper, we present an image encryption scheme based on the multi-stage chaos-based image encryption algorithm. The method works on the principle of confusion and diffusion. The proposed scheme containing both confusion and diffusion modules ar... Read More about A Secure and Lightweight Chaos Based Image Encryption Scheme.

A Highly Secured Image Encryption Scheme using Quantum Walk and Chaos (2022)
Journal Article
Kamran, M. I., Khan, M. A., Alsuhibany, S. A., Ghadi, Y. Y., Arshad, Arif, J., & Ahmad, J. (2022). A Highly Secured Image Encryption Scheme using Quantum Walk and Chaos. Computers, Materials & Continua, 73(1), 657-672. https://doi.org/10.32604/cmc.2022.02

The use of multimedia data sharing has drastically increased in the past few decades due to the revolutionary improvements in communication technologies such as the 4th generation (4G) and 5th generation (5G) etc. Researchers have proposed many image... Read More about A Highly Secured Image Encryption Scheme using Quantum Walk and Chaos.

A New Intrusion Detection System for the Internet of Things via Deep Convolutional Neural Network and Feature Engineering (2022)
Journal Article
Ullah, S., Ahmad, J., Khan, M. A., Alkhammash, E. H., Hadjouni, M., Ghadi, Y. Y., …Pitropakis, N. (2022). A New Intrusion Detection System for the Internet of Things via Deep Convolutional Neural Network and Feature Engineering. Sensors, 22(10), Article

The Internet of Things (IoT) is a widely used technology in automated network systems across the world. The impact of the IoT on different industries has occurred in recent years. Many IoT nodes collect, store, and process personal data, which is an... Read More about A New Intrusion Detection System for the Internet of Things via Deep Convolutional Neural Network and Feature Engineering.

Cyber Threat Intelligence-Based Malicious URL Detection Model Using Ensemble Learning (2022)
Journal Article
Ghaleb, F. A., Alsaedi, M., Saeed, F., Ahmad, J., & Alasli, M. (2022). Cyber Threat Intelligence-Based Malicious URL Detection Model Using Ensemble Learning. Sensors, 22(9), Article 3373. https://doi.org/10.3390/s22093373

Web applications have become ubiquitous for many business sectors due to their platform independence and low operation cost. Billions of users are visiting these applications to accomplish their daily tasks. However, many of these applications are ei... Read More about Cyber Threat Intelligence-Based Malicious URL Detection Model Using Ensemble Learning.

Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform (2022)
Journal Article
Abd, M. H., Al-Suhail, G. A., Tahir, F. R., Ali Ali, A. M., Abbood, H. A., Dashtipour, K., …Ahmad, J. (2022). Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform. Remote Sensing, 14(9), Article 1984. https://doi.org/10.3390/

There is no doubt that chaotic systems are still attractive issues in various radar applications and communication systems. In this paper, we present a new 0.3 GHz mono-static microwave chaotic radar. It includes a chaotic system based on a time-dela... Read More about Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform.

A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos-Based Quantum Map (2022)
Journal Article
Alharbi, A. R., Ahmad, J., Arshad, Shaukat, S., Masood, F., Ghadi, Y. Y., …Buchanan, W. J. (2022). A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos-Based Quantum Map. Complexity, 2022, Article 7047282. https://doi.org/10.1155/

With the increasing volume of data transmission through insecure communication channels, big data security has become one of the important concerns in the cybersecurity domain. To address these concerns and keep data safe, a robust privacy-preserving... Read More about A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos-Based Quantum Map.

Optimal Pitch Angle Controller for DFIG-Based Wind Turbine System Using Computational Optimization Techniques (2022)
Journal Article
Khurshid, A., Mughal, M. A., Othman, A., Al-Hadhrami, T., Kumar, H., Khurshid, I., …Ahmad, J. (2022). Optimal Pitch Angle Controller for DFIG-Based Wind Turbine System Using Computational Optimization Techniques. Electronics, 11(8), Article 1290. https:

With the advent of high-speed and parallel computing, the applicability of computational optimization in engineering problems has increased, with greater validation than conventional methods. Pitch angle is an effective variable in extracting maximum... Read More about Optimal Pitch Angle Controller for DFIG-Based Wind Turbine System Using Computational Optimization Techniques.

A novel image encryption scheme based on Arnold cat map, Newton-Leipnik system and Logistic Gaussian map (2022)
Journal Article
Masood, F., Boulila, W., Alsaeedi, A., Khan, J. S., Ahmad, J., Khan, M. A., & Rehman, S. U. (2022). A novel image encryption scheme based on Arnold cat map, Newton-Leipnik system and Logistic Gaussian map. Multimedia Tools and Applications, 81, 30931-3095

In the existing literature, numerous chaos-based multimedia encryption schemes have been presented. Benefiting from inherent properties such as ergodicity and key-sensitivity; this can potentially improve non-linearity in encrypted data. This paper i... Read More about A novel image encryption scheme based on Arnold cat map, Newton-Leipnik system and Logistic Gaussian map.

A federated learning framework for cyberattack detection in vehicular sensor networks (2022)
Journal Article
Driss, M., Almomani, I., e Huma, Z., & Ahmad, J. (2022). A federated learning framework for cyberattack detection in vehicular sensor networks. Complex and Intelligent Systems, 8(5), 4221-4235. https://doi.org/10.1007/s40747-022-00705-w

Vehicular Sensor Networks (VSN) introduced a new paradigm for modern transportation systems by improving traffic management and comfort. However, the increasing adoption of smart sensing technologies with the Internet of Things (IoT) made VSN a high-... Read More about A federated learning framework for cyberattack detection in vehicular sensor networks.

A Smart and Robust Automatic Inspection of Printed Labels Using an Image Hashing Technique (2022)
Journal Article
Khan, M. A., Ahmed, F., Khan, M. D., Ahmad, J., Kumar, H., & Pitropakis, N. (2022). A Smart and Robust Automatic Inspection of Printed Labels Using an Image Hashing Technique. Electronics, 11(6), Article 955. https://doi.org/10.3390/electronics11060955

This work is focused on the development of a smart and automatic inspection system for printed labels. This is a challenging problem to solve since the collected labels are typically subjected to a variety of geometric and non-geometric distortions.... Read More about A Smart and Robust Automatic Inspection of Printed Labels Using an Image Hashing Technique.

Dynamic S-Box and PWLCM-Based Robust Watermarking Scheme (2022)
Journal Article
Sher Khan, J., Koç Kayhan, S., Siddiq Ahmed, S., Ahmad, J., Ayesha Siddiqa, H., Ahmed, F., …Al Dubai, A. (2022). Dynamic S-Box and PWLCM-Based Robust Watermarking Scheme. Wireless Personal Communications, 125, 513-530. https://doi.org/10.1007/s11277-02

Due to the increased number of cyberattacks, numerous researchers are motivated towards the design of such schemes that can hide digital information in a signal. Watermarking is one of the promising technologies that can protect digital information.... Read More about Dynamic S-Box and PWLCM-Based Robust Watermarking Scheme.

Evolution towards Smart and Software-Defined Internet of Things (2022)
Journal Article
Abid, M. A., Afaqui, N., Khan, M. A., Akhtar, M. W., Malik, A. W., Munir, A., …Shabir, B. (2022). Evolution towards Smart and Software-Defined Internet of Things. AI, 3(1), 100-123. https://doi.org/10.3390/ai3010007

The Internet of Things (IoT) is a mesh network of interconnected objects with unique identifiers that can transmit data and communicate with one another without the need for human intervention. The IoT has brought the future closer to us. It has open... Read More about Evolution towards Smart and Software-Defined Internet of Things.

Detecting Alzheimer’s Disease Using Machine Learning Methods (2022)
Presentation / Conference Contribution
Dashtipour, K., Taylor, W., Ansari, S., Zahid, A., Gogate, M., Ahmad, J., Assaleh, K., Arshad, K., Ali Imran, M., & Abbasi, Q. (2021, October). Detecting Alzheimer’s Disease Using Machine Learning Methods. Presented at 16th EAI International Conference,

As the world is experiencing population growth, the portion of the older people, aged 65 and above, is also growing at a faster rate. As a result, the dementia with Alzheimer’s disease is expected to increase rapidly in the next few years. Currently,... Read More about Detecting Alzheimer’s Disease Using Machine Learning Methods.

Comparing the Performance of Different Classifiers for Posture Detection (2022)
Presentation / Conference Contribution
Suresh Kumar, S., Dashtipour, K., Gogate, M., Ahmad, J., Assaleh, K., Arshad, K., Imran, M. A., Abbasi, Q., & Ahmad, W. (2021, October). Comparing the Performance of Different Classifiers for Posture Detection. Presented at 16th EAI International Conferen

Human Posture Classification (HPC) is used in many fields such as human computer interfacing, security surveillance, rehabilitation, remote monitoring, and so on. This paper compares the performance of different classifiers in the detection of 3 post... Read More about Comparing the Performance of Different Classifiers for Posture Detection.

HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles (2022)
Journal Article
Ullah, S., Khan, M. A., Ahmad, J., Jamal, S. S., e Huma, Z., Hassan, M. T., …Buchanan, W. J. (2022). HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles. Sensors, 22(4), Article 1340. https://doi.org/10.3390/

Internet of Vehicles (IoV) is an application of the Internet of Things (IoT) network that connects smart vehicles to the internet, and vehicles with each other. With the emergence of IoV technology, customers have placed great attention on smart vehi... Read More about HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles.

Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers (2022)
Presentation / Conference Contribution
Ali, H., Papadopoulos, P., Ahmad, J., Pit, N., Jaroucheh, Z., & Buchanan, W. J. (2021, December). Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers. Presented at IEEE SINCONF: 14th International Conference on Security of

Threat information sharing is considered as one of the proactive defensive approaches for enhancing the overall security of trusted partners. Trusted partner organizations can provide access to past and current cybersecurity threats for reducing the... Read More about Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers.

Chest X-ray Classification for the Detection of COVID-19 Using Deep Learning Techniques (2022)
Journal Article
Khan, E., Rehman, M. Z. U., Ahmed, F., Alfouzan, F. A., Alzahrani, N. M., & Ahmad, J. (2022). Chest X-ray Classification for the Detection of COVID-19 Using Deep Learning Techniques. Sensors, 22(3), Article 1211. https://doi.org/10.3390/s22031211

Recent technological developments pave the path for deep learning-based techniques to be used in almost every domain of life. The precision of deep learning techniques make it possible for these to be used in the medical field for the classification... Read More about Chest X-ray Classification for the Detection of COVID-19 Using Deep Learning Techniques.

Semantic Segmentation and Edge Detection—Approach to Road Detection in Very High Resolution Satellite Images (2022)
Journal Article
Ghandorh, H., Boulila, W., Masood, S., Koubaa, A., Ahmed, F., & Ahmad, J. (2022). Semantic Segmentation and Edge Detection—Approach to Road Detection in Very High Resolution Satellite Images. Remote Sensing, 14(3), Article 613. https://doi.org/10.3390/r

Road detection technology plays an essential role in a variety of applications, such as urban planning, map updating, traffic monitoring and automatic vehicle navigation. Recently, there has been much development in detecting roads in high-resolution... Read More about Semantic Segmentation and Edge Detection—Approach to Road Detection in Very High Resolution Satellite Images.

Ransomware: Analysing the Impact on Windows Active Directory Domain Services (2022)
Journal Article
McDonald, G., Papadopoulos, P., Pitropakis, N., Ahmad, J., & Buchanan, W. J. (2022). Ransomware: Analysing the Impact on Windows Active Directory Domain Services. Sensors, 22(3), Article 953. https://doi.org/10.3390/s22030953

Ransomware has become an increasingly popular type of malware across the past decade and continues to rise in popularity due to its high profitability. Organisations and enterprises have become prime targets for ransomware as they are more likely to... Read More about Ransomware: Analysing the Impact on Windows Active Directory Domain Services.

A Novel Chaotic Permutation-Substitution Image Encryption Scheme Based on Logistic Map and Random Substitution (2022)
Journal Article
Arif, J., Khan, M. A., Ghaleb, B., Ahmad, J., Munir, A., Rashid, U., & Al-Dubai, A. Y. (2022). A Novel Chaotic Permutation-Substitution Image Encryption Scheme Based on Logistic Map and Random Substitution. IEEE Access, 10, 12966-12982. https://doi.org/10

Privacy is a serious concern related to sharing videos or images among people over the Internet. As a method to preserve images’ privacy, chaos-based image encryption algorithms have been used widely to fulfil such a requirement. However, these algor... Read More about A Novel Chaotic Permutation-Substitution Image Encryption Scheme Based on Logistic Map and Random Substitution.

Multiple Participants’ Discrete Activity Recognition in a Well-Controlled Environment Using Universal Software Radio Peripheral Wireless Sensing (2022)
Journal Article
Saeed, U., Yaseen Shah, S., Aziz Shah, S., Liu, H., Alhumaidi Alotaibi, A., Althobaiti, T., …H. Abbasi, Q. (2022). Multiple Participants’ Discrete Activity Recognition in a Well-Controlled Environment Using Universal Software Radio Peripheral Wireless

Wireless sensing is the utmost cutting-edge way of monitoring different health-related activities and, concurrently, preserving most of the privacy of individuals. To meet future needs, multi-subject activity monitoring is in demand, whether it is fo... Read More about Multiple Participants’ Discrete Activity Recognition in a Well-Controlled Environment Using Universal Software Radio Peripheral Wireless Sensing.

Multiple Participants’ Discrete Activity Recognition in a Well-Controlled Environment Using Universal Software Radio Peripheral Wireless Sensing (2022)
Journal Article
Saeed, U., Yaseen Shah, S., Aziz Shah, S., Liu, H., Alhumaidi Alotaibi, A., Althobaiti, T., …Abbasi, Q. H. (2022). Multiple Participants’ Discrete Activity Recognition in a Well-Controlled Environment Using Universal Software Radio Peripheral Wireless

Wireless sensing is the utmost cutting-edge way of monitoring different health-related activities and, concurrently, preserving most of the privacy of individuals. To meet future needs, multi-subject activity monitoring is in demand, whether it is fo... Read More about Multiple Participants’ Discrete Activity Recognition in a Well-Controlled Environment Using Universal Software Radio Peripheral Wireless Sensing.

Novel Privacy Preserving Non-Invasive Sensing-Based Diagnoses of Pneumonia Disease Leveraging Deep Network Model (2022)
Journal Article
Rehman, M. U., Shafique, A., Khan, K. H., Khalid, S., Alotaibi, A. A., Althobaiti, T., …Abbasi, Q. H. (2022). Novel Privacy Preserving Non-Invasive Sensing-Based Diagnoses of Pneumonia Disease Leveraging Deep Network Model. Sensors, 22(2), Article 461.

This article presents non-invasive sensing-based diagnoses of pneumonia disease, exploiting a deep learning model to make the technique non-invasive coupled with security preservation. Sensing and securing healthcare and medical images such as X-rays... Read More about Novel Privacy Preserving Non-Invasive Sensing-Based Diagnoses of Pneumonia Disease Leveraging Deep Network Model.

Machine learning empowered COVID-19 patient monitoring using non-contact sensing: An extensive review (2022)
Journal Article
Saeed, U., Shah, S. Y., Ahmad, J., Imran, M. A., Abbasi, Q. H., & Shah, S. A. (2022). Machine learning empowered COVID-19 patient monitoring using non-contact sensing: An extensive review. Journal of Pharmaceutical Analysis, 12(2), 193-204. https://doi.or

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which caused the coronavirus disease 2019 (COVID-19) pandemic, has affected more than 400 million people worldwide. With the recent rise of new Delta and Omicron variants, the efficacy... Read More about Machine learning empowered COVID-19 patient monitoring using non-contact sensing: An extensive review.

Browsers’ Private Mode: Is It What We Were Promised? (2021)
Journal Article
Hughes, K., Papadopoulos, P., Pitropakis, N., Smales, A., Ahmad, J., & Buchanan, W. J. (2021). Browsers’ Private Mode: Is It What We Were Promised?. Computers, 10(12), Article 165. https://doi.org/10.3390/computers10120165

Web browsers are one of the most used applications on every computational device in our days. Hence, they play a pivotal role in any forensic investigation and help determine if nefarious or suspicious activity has occurred on that device. Our study... Read More about Browsers’ Private Mode: Is It What We Were Promised?.

A new color image encryption technique using DNA computing and Chaos-based substitution box (2021)
Journal Article
Ahmad, J., Masood, F., Masood, J., Zhang, L., Shaukat Jamal, S., Boulila, W., …Khan, F. A. (2022). A new color image encryption technique using DNA computing and Chaos-based substitution box. Soft Computing, 26(16), 7461-7477. https://doi.org/10.1007/s0

In many cases, images contain sensitive information and patterns that require secure processing to avoid risk. It can be accessed by unauthorized users who can illegally exploit them to threaten the safety of people’s life and property. Protecting th... Read More about A new color image encryption technique using DNA computing and Chaos-based substitution box.

Intrusion Detection Framework for the Internet of Things Using a Dense Random Neural Network (2021)
Journal Article
Latif, S., Huma, Z. E., Jamal, S. S., Ahmed, F., Ahmad, J., Zahid, A., …Abbasi, Q. H. (2022). Intrusion Detection Framework for the Internet of Things Using a Dense Random Neural Network. IEEE Transactions on Industrial Informatics, 18(9), 6435-6444. ht

The Internet of Things (IoT) devices, networks, and applications have become an integral part of modern societies. Despite their social, economic, and industrial benefits, these devices and networks are frequently targeted by cybercriminals. Hence, I... Read More about Intrusion Detection Framework for the Internet of Things Using a Dense Random Neural Network.

Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions (2021)
Journal Article
Latif, S., Driss, M., Boulila, W., Huma, Z. E., Jamal, S. S., Idrees, Z., & Ahmad, J. (2021). Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future D

The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast communication protocols, and efficient cybersecurity mechanisms to improve industrial processes and applications. In large industrial networks, smart devices... Read More about Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions.

Noninvasive Detection of Respiratory Disorder Due to COVID-19 at the Early Stages in Saudi Arabia (2021)
Journal Article
Boulila, W., Shah, S. A., Ahmad, J., Driss, M., Ghandorh, H., Alsaeedi, A., …Saeed, F. (2021). Noninvasive Detection of Respiratory Disorder Due to COVID-19 at the Early Stages in Saudi Arabia. Electronics, 10(21), Article 2701. https://doi.org/10.3390/

The Kingdom of Saudi Arabia has suffered from COVID-19 disease as part of the global pandemic due to severe acute respiratory syndrome coronavirus 2. The economy of Saudi Arabia also suffered a heavy impact. Several measures were taken to help mitiga... Read More about Noninvasive Detection of Respiratory Disorder Due to COVID-19 at the Early Stages in Saudi Arabia.

A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT (2021)
Journal Article
Almas Khan, M., Khan, M. A., Ullah Jan, S., Ahmad, J., Jamal, S. S., Shah, A. A., Pitropakis, N., Buchanan, W. J., Alonistioti, N., Panagiotakis, S., & Markakis, E. K. (2021). A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT. Sensors,

A large number of smart devices in Internet of Things (IoT) environments communicate via different messaging protocols. Message Queuing Telemetry Transport (MQTT) is a widely used publish–subscribe-based protocol for the communication of sensor or ev... Read More about A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT.

Dynamic Hand Gesture Recognition Using 3D-CNN and LSTM Networks (2021)
Journal Article
Ur Rehman, M., Ahmed, F., Attique Khan, M., Tariq, U., Abdulaziz Alfouzan, F., M. Alzahrani, N., & Ahmad, J. (2021). Dynamic Hand Gesture Recognition Using 3D-CNN and LSTM Networks. Computers, Materials & Continua, 70(3), 4675-4690. https://doi.org/10.326

Recognition of dynamic hand gestures in real-time is a difficult task because the system can never know when or from where the gesture starts and ends in a video stream. Many researchers have been working on vision-based gesture recognition due to it... Read More about Dynamic Hand Gesture Recognition Using 3D-CNN and LSTM Networks.

Microservices in IoT Security: Current Solutions, Research Challenges, and Future Directions (2021)
Presentation / Conference Contribution
Driss, M., Hasan, D., Boulila, W., & Ahmad, J. (2021). Microservices in IoT Security: Current Solutions, Research Challenges, and Future Directions. Procedia Computer Science, 192, 2385-2395. https://doi.org/10.1016/j.procs.2021.09.007

In recent years, the Internet of Things (IoT) technology has led to the emergence of multiple smart applications in different vital sectors including healthcare, education, agriculture, energy management, etc. IoT aims to interconnect several intelli... Read More about Microservices in IoT Security: Current Solutions, Research Challenges, and Future Directions.

Discrete Human Activity Recognition and Fall Detection by Combining FMCW RADAR Data of Heterogeneous Environments for Independent Assistive Living (2021)
Journal Article
Saeed, U., Shah, S. Y., Shah, S. A., Ahmad, J., Alotaibi, A. A., Althobaiti, T., …Abbasi, Q. H. (2021). Discrete Human Activity Recognition and Fall Detection by Combining FMCW RADAR Data of Heterogeneous Environments for Independent Assistive Living. E

Human activity monitoring is essential for a variety of applications in many fields, particularly healthcare. The goal of this research work is to develop a system that can effectively detect fall/collapse and classify other discrete daily living act... Read More about Discrete Human Activity Recognition and Fall Detection by Combining FMCW RADAR Data of Heterogeneous Environments for Independent Assistive Living.

Classification of Citrus Plant Diseases Using Deep Transfer Learning (2021)
Journal Article
Zia Ur Rehman, M., Ahmed, F., Attique Khan, M., Tariq, U., Shaukat Jamal, S., Ahmad, J., & Hussain, I. (2022). Classification of Citrus Plant Diseases Using Deep Transfer Learning. Computers, Materials & Continua, 70(1), 1401-1417. https://doi.org/10.3260

In recent years, the field of deep learning has played an important role towards automatic detection and classification of diseases in vegetables and fruits. This in turn has helped in improving the quality and production of vegetables and fruits. Ci... Read More about Classification of Citrus Plant Diseases Using Deep Transfer Learning.

A New Ensemble-Based Intrusion Detection System for Internet of Things (2021)
Journal Article
Abbas, A., Khan, M. A., Latif, S., Ajaz, M., Shah, A. A., & Ahmad, J. (2022). A New Ensemble-Based Intrusion Detection System for Internet of Things. Arabian Journal for Science and Engineering, 47, 1805-1819. https://doi.org/10.1007/s13369-021-06086-5

The domain of Internet of Things (IoT) has witnessed immense adaptability over the last few years by drastically transforming human lives to automate their ordinary daily tasks. This is achieved by interconnecting heterogeneous physical devices with... Read More about A New Ensemble-Based Intrusion Detection System for Internet of Things.

Detection of COVID-19 Using Transfer Learning and Grad-CAM Visualization on Indigenously Collected X-ray Dataset (2021)
Journal Article
Umair, M., Khan, M. S., Ahmed, F., Baothman, F., Alqahtani, F., Alian, M., & Ahmad, J. (2021). Detection of COVID-19 Using Transfer Learning and Grad-CAM Visualization on Indigenously Collected X-ray Dataset. Sensors, 21(17), Article 5813. https://doi.org

The COVID-19 outbreak began in December 2019 and has dreadfully affected our lives since then. More than three million lives have been engulfed by this newest member of the corona virus family. With the emergence of continuously mutating variants of... Read More about Detection of COVID-19 Using Transfer Learning and Grad-CAM Visualization on Indigenously Collected X-ray Dataset.

Blockchain technology for the industrial Internet of Things: A comprehensive survey on security challenges, architectures, applications, and future research directions (2021)
Journal Article
Latif, S., Idrees, Z., e Huma, Z., & Ahmad, J. (2021). Blockchain technology for the industrial Internet of Things: A comprehensive survey on security challenges, architectures, applications, and future research directions. Transactions on Emerging Teleco

The blockchain has emerged as an innovative and powerful technology that shows the tremendous potential to enhance the smart industrial frameworks by providing encryption, immutable storage, and decentralization. In the past few years, several applic... Read More about Blockchain technology for the industrial Internet of Things: A comprehensive survey on security challenges, architectures, applications, and future research directions.

Wireless Channel Modelling for Identifying Six Types of Respiratory Patterns With SDR Sensing and Deep Multilayer Perceptron (2021)
Journal Article
Saeed, U., Shah, S. Y., Zahid, A., Ahmad, J., Imran, M. A., Abbasi, Q. H., & Shah, S. A. (2021). Wireless Channel Modelling for Identifying Six Types of Respiratory Patterns With SDR Sensing and Deep Multilayer Perceptron. IEEE Sensors Journal, 21(18), 20

Contactless or non-invasive technology has a significant impact on healthcare applications such as the prediction of COVID-19 symptoms. Non-invasive methods are essential especially during the COVID-19 pandemic as they minimise the burden on healthca... Read More about Wireless Channel Modelling for Identifying Six Types of Respiratory Patterns With SDR Sensing and Deep Multilayer Perceptron.

Infrared Sensing Based Non-Invasive Initial Diagnosis of Chronic Liver Disease Using Ensemble Learning (2021)
Journal Article
Rehman, M. U., Najam, S., Khalid, S., Shafique, A., Alqahtani, F., Baothman, F., …Ahmad, J. (2021). Infrared Sensing Based Non-Invasive Initial Diagnosis of Chronic Liver Disease Using Ensemble Learning. IEEE Sensors Journal, 21(17), 19395-19406. https:

The liver is a vital human body organ and its functionality can be degraded by several diseases such as hepatitis, fatty liver disease, and liver cancer and so forth. Hence, the early diagnosis of liver diseases is extremely crucial for saving human... Read More about Infrared Sensing Based Non-Invasive Initial Diagnosis of Chronic Liver Disease Using Ensemble Learning.

An Efficient Approach Based on Privacy-Preserving Deep Learning for Satellite Image Classification (2021)
Journal Article
Alkhelaiwi, M., Boulila, W., Ahmad, J., Koubaa, A., & Driss, M. (2021). An Efficient Approach Based on Privacy-Preserving Deep Learning for Satellite Image Classification. Remote Sensing, 13(11), Article 2221. https://doi.org/10.3390/rs13112221

Satellite images have drawn increasing interest from a wide variety of users, including business and government, ever since their increased usage in important fields ranging from weather, forestry and agriculture to surface changes and biodiversity m... Read More about An Efficient Approach Based on Privacy-Preserving Deep Learning for Satellite Image Classification.

Design of Portable Exoskeleton Forearm for Rehabilitation of Monoparesis Patients Using Tendon Flexion Sensing Mechanism for Health Care Applications (2021)
Journal Article
Imtiaz, M. S. B., Babar Ali, C., Kausar, Z., Shah, S. Y., Shah, S. A., Ahmad, J., …Abbasi, Q. H. (2021). Design of Portable Exoskeleton Forearm for Rehabilitation of Monoparesis Patients Using Tendon Flexion Sensing Mechanism for Health Care Application

Technology plays a vital role in patient rehabilitation, improving the quality of life of an individual. The increase in functional independence of disabled individuals requires adaptive and commercially available solutions. The use of sensor-based t... Read More about Design of Portable Exoskeleton Forearm for Rehabilitation of Monoparesis Patients Using Tendon Flexion Sensing Mechanism for Health Care Applications.

A novel CNN-LSTM-based approach to predict urban expansion (2021)
Journal Article
Boulila, W., Ghandorh, H., Khan, M. A., Ahmed, F., & Ahmad, J. (2021). A novel CNN-LSTM-based approach to predict urban expansion. Ecological Informatics, 64, Article 101325. https://doi.org/10.1016/j.ecoinf.2021.101325

Time-series remote sensing data offer a rich source of information that can be used in a wide range of applications, from monitoring changes in land cover to surveillance of crops, coastal changes, flood risk assessment, and urban sprawl. In this pap... Read More about A novel CNN-LSTM-based approach to predict urban expansion.

Granular Data Access Control with a Patient-Centric Policy Update for Healthcare (2021)
Journal Article
Khan, F., Khan, S., Tahir, S., Ahmad, J., Tahir, H., & Shah, S. A. (2021). Granular Data Access Control with a Patient-Centric Policy Update for Healthcare. Sensors, 21(10), Article 3556. https://doi.org/10.3390/s21103556

Healthcare is a multi-actor environment that requires independent actors to have a different view of the same data, hence leading to different access rights. Ciphertext Policy-Attribute-based Encryption (CP-ABE) provides a one-to-many access control... Read More about Granular Data Access Control with a Patient-Centric Policy Update for Healthcare.

A Lightweight Chaos-Based Medical Image Encryption Scheme Using Random Shuffling and XOR Operations (2021)
Journal Article
Masood, F., Driss, M., Boulila, W., Ahmad, J., ur Rehman, S., Jan, S. U., Qayyum, A., & Buchanan, W. J. (2022). A Lightweight Chaos-Based Medical Image Encryption Scheme Using Random Shuffling and XOR Operations. Wireless Personal Communications, 127, 140

Medical images possess significant importance in diagnostics when it comes to healthcare systems. These images contain confidential and sensitive information such as patients’ X-rays, ultrasounds, computed tomography scans, brain images, and magnetic... Read More about A Lightweight Chaos-Based Medical Image Encryption Scheme Using Random Shuffling and XOR Operations.

Application of Artificial Neural Network in Predicting Flashover Behaviour of Outdoor Insulators under Polluted Conditions (2021)
Presentation / Conference Contribution
Sajjad, U., Arshad, Ahmad, J., & Shoaib, S. (2021). Application of Artificial Neural Network in Predicting Flashover Behaviour of Outdoor Insulators under Polluted Conditions. In 2021 IEEE Conference of Russian Young Researchers in Electrical and Electro

Safe and reliable delivery of power through transmission lines mainly depends on the quality condition of the high voltage insulators. In the last few decades, demand in polymeric insulator has been dramatically increased due to their advanced perfor... Read More about Application of Artificial Neural Network in Predicting Flashover Behaviour of Outdoor Insulators under Polluted Conditions.

A Hybrid Deep Random Neural Network for Cyberattack Detection in the Industrial Internet of Things (2021)
Journal Article
Huma, Z. E., Latif, S., Ahmad, J., Idrees, Z., Ibrar, A., Zou, Z., …Baothman, F. (2021). A Hybrid Deep Random Neural Network for Cyberattack Detection in the Industrial Internet of Things. IEEE Access, 9, 55595-55605. https://doi.org/10.1109/access.2021

The Industrial Internet of Things (IIoT) refers to the use of traditional Internet of Things (IoT) concepts in industrial sectors and applications. IIoT has several applications in smart homes, smart cities, smart grids, connected cars, and supply ch... Read More about A Hybrid Deep Random Neural Network for Cyberattack Detection in the Industrial Internet of Things.

An experimental analysis of attack classification using machine learning in IoT networks (2021)
Journal Article
Churcher, A., Ullah, R., Ahmad, J., Ur Rehman, S., Masood, F., Gogate, M., Alqahtani, F., Nour, B., & Buchanan, W. J. (2021). An experimental analysis of attack classification using machine learning in IoT networks. Sensors, 21(2), Article 446. https://d

In recent years, there has been a massive increase in the amount of Internet of Things (IoT) devices as well as the data generated by such devices. The participating devices in IoT networks can be problematic due to their resource-constrained nature,... Read More about An experimental analysis of attack classification using machine learning in IoT networks.

Detecting the Security Level of Various Cryptosystems Using Machine Learning Models (2020)
Journal Article
Shafique, A., Ahmed, J., Boulila, W., Ghandorh, H., Ahmad, J., & Rehman, M. U. (2021). Detecting the Security Level of Various Cryptosystems Using Machine Learning Models. IEEE Access, 9, 9383-9393. https://doi.org/10.1109/access.2020.3046528

With recent advancements in multimedia technologies, the security of digital data has become a critical issue. To overcome the vulnerabilities of current security protocols, researchers tend to focus their efforts on modifying existing protocols. Ove... Read More about Detecting the Security Level of Various Cryptosystems Using Machine Learning Models.

A blockchain-based architecture for secure and trustworthy operations in the industrial Internet of Things (2020)
Journal Article
Latif, S., Idrees, Z., Ahmad, J., Zheng, L., & Zou, Z. (2021). A blockchain-based architecture for secure and trustworthy operations in the industrial Internet of Things. Journal of Industrial Information Integration, 21, Article 100190. https://doi.org/1

The industrial Internet of Things (IIoT) plays an important role in the industrial sector, where secure, scalable, and easily adopted technologies are being implemented for the smart industry. The traditional IIoT architectures are generally based on... Read More about A blockchain-based architecture for secure and trustworthy operations in the industrial Internet of Things.

Prediction of Critical Flashover Voltage of High Voltage Insulators Leveraging Bootstrap Neural Network (2020)
Journal Article
Niazi, M. T. K., Arshad, Ahmad, J., Alqahtani, F., Baotham, F. A., & Abu-Amara, F. (2020). Prediction of Critical Flashover Voltage of High Voltage Insulators Leveraging Bootstrap Neural Network. Electronics, 9(10), Article 1620. https://doi.org/10.3390/e

Understanding the flashover performance of the outdoor high voltage insulator has been in the interest of many researchers recently. Various studies have been performed to investigate the critical flashover voltage of outdoor high voltage insulators... Read More about Prediction of Critical Flashover Voltage of High Voltage Insulators Leveraging Bootstrap Neural Network.

EEG-Based Neonatal Sleep-Wake Classification Using Multilayer Perceptron Neural Network (2020)
Journal Article
Abbasi, S. F., Ahmad, J., Tahir, A., Awais, M., Chen, C., Irfan, M., …Chen, W. (2020). EEG-Based Neonatal Sleep-Wake Classification Using Multilayer Perceptron Neural Network. IEEE Access, 8, 183025-183034. https://doi.org/10.1109/access.2020.3028182

Objective: Classification of sleep-wake states using multichannel electroencephalography (EEG) data that reliably work for neonates. Methods: A deep multilayer perceptron (MLP) neural network is developed to classify sleep-wake states using multichan... Read More about EEG-Based Neonatal Sleep-Wake Classification Using Multilayer Perceptron Neural Network.

Privacy-Preserving Wandering Behavior Sensing in Dementia Patients Using Modified Logistic and Dynamic Newton Leipnik Maps (2020)
Journal Article
Shah, S. A., Ahmad, J., Masood, F., Shah, S. Y., Pervaiz, H., Taylor, W., …Abbasi, Q. H. (2021). Privacy-Preserving Wandering Behavior Sensing in Dementia Patients Using Modified Logistic and Dynamic Newton Leipnik Maps. IEEE Sensors Journal, 21(3), 366

The health status of an elderly person can be identified by examining the additive effects of aging along disease linked to it and can lead to the ’unstable incapacity’. This health status is essentially determined by the apparent decline of independ... Read More about Privacy-Preserving Wandering Behavior Sensing in Dementia Patients Using Modified Logistic and Dynamic Newton Leipnik Maps.

DNA and Plaintext Dependent Chaotic Visual Selective Image Encryption (2020)
Journal Article
Khan, J. S., Boulila, W., Ahmad, J., Rubaiee, S., Rehman, A. U., Alroobaea, R., & Buchanan, W. J. (2020). DNA and Plaintext Dependent Chaotic Visual Selective Image Encryption. IEEE Access, 8, 159732-159744. https://doi.org/10.1109/access.2020.3020917

Visual selective image encryption can both improve the efficiency of the image encryption algorithm and reduce the frequency and severity of attacks against data. In this article, a new form of encryption is proposed based on keys derived from Deoxyri... Read More about DNA and Plaintext Dependent Chaotic Visual Selective Image Encryption.

Forecasting Flashover Parameters of Polymeric Insulators under Contaminated Conditions Using the Machine Learning Technique (2020)
Journal Article
Arshad, Ahmad, J., Tahir, A., Stewart, B. G., & Nekahi, A. (2020). Forecasting Flashover Parameters of Polymeric Insulators under Contaminated Conditions Using the Machine Learning Technique. Energies, 13(15), Article 3889. https://doi.org/10.3390/en13153

There is a vital need to understand the flashover process of polymeric insulators for safe and reliable power system operation. This paper provides a rigorous investigation of forecasting the flashover parameters of High Temperature Vulcanized (HTV)... Read More about Forecasting Flashover Parameters of Polymeric Insulators under Contaminated Conditions Using the Machine Learning Technique.

Chaos-Based Confusion and Diffusion of Image Pixels Using Dynamic Substitution (2020)
Journal Article
Qayyum, A., Ahmad, J., Boulila, W., Rubaiee, S., Arshad, Masood, F., Khan, F., & Buchanan, W. J. (2020). Chaos-Based Confusion and Diffusion of Image Pixels Using Dynamic Substitution. IEEE Access, 8, 140876-140895. https://doi.org/10.1109/access.2020.301

The evolution of wireless and mobile communication from 0G to the upcoming 5G gives riseto data sharing through the Internet. This data transfer via open public networks are susceptible to severaltypes of attacks. Encryption is a method that can prot... Read More about Chaos-Based Confusion and Diffusion of Image Pixels Using Dynamic Substitution.

5G-FOG: Freezing of Gait Identification in Multi-Class Softmax Neural Network Exploiting 5G Spectrum (2020)
Presentation / Conference Contribution
Khan, J. S., Tahir, A., Ahmad, J., Shah, S. A., Abbasi, Q. H., Russell, G., & Buchanan, W. (2020, July). 5G-FOG: Freezing of Gait Identification in Multi-Class Softmax Neural Network Exploiting 5G Spectrum. Presented at 2020 Computing Conference, London

Freezing of gait (FOG) is one of the most incapacitating and disconcerting symptom in Parkinson's disease (PD). FOG is the result of neural control disorder and motor impairments, which severely impedes forward locomotion. This paper presents the exp... Read More about 5G-FOG: Freezing of Gait Identification in Multi-Class Softmax Neural Network Exploiting 5G Spectrum.

Sensor Fusion for Identification of Freezing of Gait Episodes Using Wi-Fi and Radar Imaging (2020)
Journal Article
Shah, S. A., Tahir, A., Ahmad, J., Zahid, A., Pervaiz, H., Shah, S. Y., …Abbasi, Q. H. (2020). Sensor Fusion for Identification of Freezing of Gait Episodes Using Wi-Fi and Radar Imaging. IEEE Sensors Journal, 20(23), 14410-14422. https://doi.org/10.110

Parkinson’s disease (PD) is a progressive and neurodegenerative condition causing motor impairments. One of the major motor related impairments that present biggest challenge is freezing of gait (FOG) in Parkinson’s patients. In FOG episode, the pati... Read More about Sensor Fusion for Identification of Freezing of Gait Episodes Using Wi-Fi and Radar Imaging.

A Novel Privacy Approach of Digital Aerial Images Based on Mersenne Twister Method with DNA Genetic Encoding and Chaos (2020)
Journal Article
Masood, F., Boulila, W., Ahmad, J., Arshad, A., Sankar, S., Rubaiee, S., & Buchanan, W. J. (2020). A Novel Privacy Approach of Digital Aerial Images Based on Mersenne Twister Method with DNA Genetic Encoding and Chaos. Remote Sensing, 12(11), Article 1893

Aerial photography involves capturing images from aircraft and other flying objects, including Unmanned Aerial Vehicles (UAV). Aerial images are used in many fields and can contain sensitive information that requires secure processing. We proposed an... Read More about A Novel Privacy Approach of Digital Aerial Images Based on Mersenne Twister Method with DNA Genetic Encoding and Chaos.

A Novel Attack Detection Scheme for the Industrial Internet of Things Using a Lightweight Random Neural Network (2020)
Journal Article
Latif, S., Zou, Z., Idrees, Z., & Ahmad, J. (2020). A Novel Attack Detection Scheme for the Industrial Internet of Things Using a Lightweight Random Neural Network. IEEE Access, 8, 89337-89350. https://doi.org/10.1109/access.2020.2994079

The Industrial Internet of Things (IIoT) brings together many sensors, machines, industrial applications, databases, services, and people at work. The IIoT is improving our lives in several ways including smarter cities, agriculture, and e-healthcare... Read More about A Novel Attack Detection Scheme for the Industrial Internet of Things Using a Lightweight Random Neural Network.

Mobility Prediction-Based Optimisation and Encryption of Passenger Traffic-Flows Using Machine Learning (2020)
Journal Article
Asad, S. M., Ahmad, J., Hussain, S., Zoha, A., Abbasi, Q. H., & Imran, M. A. (2020). Mobility Prediction-Based Optimisation and Encryption of Passenger Traffic-Flows Using Machine Learning. Sensors, 20(9), Article 2629. https://doi.org/10.3390/s20092629

Information and Communication Technology (ICT) enabled optimisation of train’s passenger traffic flows is a key consideration of transportation under Smart City planning (SCP). Traditional mobility prediction based optimisation and encryption approac... Read More about Mobility Prediction-Based Optimisation and Encryption of Passenger Traffic-Flows Using Machine Learning.

Energy demand forecasting of buildings using random neural networks (2020)
Journal Article
Ahmad, J., Tahir, A., Larijani, H., Ahmed, F., Aziz Shah, S., Hall, A. J., & Buchanan, W. J. (2020). Energy demand forecasting of buildings using random neural networks. Journal of Intelligent and Fuzzy Systems, 38(4), 4753-4765. https://doi.org/10.3233/j

Energy uncertainty and ecological pressures have contributed to a high volatility in energy demand and consumption. The building sector accounts for 30 to 40% of the total global energy consumption. There is a high demand for novel techniques and via... Read More about Energy demand forecasting of buildings using random neural networks.

Chaos‐based privacy preserving vehicle safety protocol for 5G Connected Autonomous Vehicle networks (2020)
Journal Article
Ansari, S., Ahmad, J., Aziz Shah, S., Kashif Bashir, A., Boutaleb, T., & Sinanovic, S. (2020). Chaos‐based privacy preserving vehicle safety protocol for 5G Connected Autonomous Vehicle networks. Transactions on Emerging Telecommunications Technologies,

There is a high demand for secure and reliable communications for Connected Autonomous Vehicles (CAVs) in the automotive industry. Privacy and security are key issues in CAVs, where network attacks can result in fatal accidents. The computational tim... Read More about Chaos‐based privacy preserving vehicle safety protocol for 5G Connected Autonomous Vehicle networks.

Robust Image Hashing Scheme using Laplacian Pyramids (2020)
Journal Article
Hamid, H., Ahmed, F., & Ahmad, J. (2020). Robust Image Hashing Scheme using Laplacian Pyramids. Computers and Electrical Engineering, 84, Article 106648. https://doi.org/10.1016/j.compeleceng.2020.106648

Due to tremendous growth in multimedia applications and services, people can easily create, distribute, broadcast and store information. The fact that multimedia content can be easily copied and tampered has motivated a large number of researchers to... Read More about Robust Image Hashing Scheme using Laplacian Pyramids.

Privacy-Preserving Non-Wearable Occupancy Monitoring System Exploiting Wi-Fi Imaging for Next-Generation Body Centric Communication (2020)
Journal Article
Aziz Shah, S., Ahmad, J., Tahir, A., Ahmed, F., Russell, G., Shah, S. Y., Buchanan, W., & Abbasi, Q. H. (2020). Privacy-Preserving Non-Wearable Occupancy Monitoring System Exploiting Wi-Fi Imaging for Next-Generation Body Centric Communication. Micromachi

Nano-scaled structures, wireless sensing, wearable devices, and wireless communications systems are anticipated to support the development of new next-generation technologies in the near future. Exponential rise in future Radio-Frequency (RF) sensing... Read More about Privacy-Preserving Non-Wearable Occupancy Monitoring System Exploiting Wi-Fi Imaging for Next-Generation Body Centric Communication.

A Novel Secure Occupancy Monitoring Scheme Based on Multi-Chaos Mapping (2020)
Journal Article
Ahmad, J., Masood, F., Shah, S. A., Jamal, S. S., & Hussain, I. (2020). A Novel Secure Occupancy Monitoring Scheme Based on Multi-Chaos Mapping. Symmetry, 12(3), https://doi.org/10.3390/sym12030350

Smart building control, managing queues for instant points of service, security systems, and customer support can benefit from the number of occupants information known as occupancy. Due to interrupted real-time continuous monitoring capabilities of... Read More about A Novel Secure Occupancy Monitoring Scheme Based on Multi-Chaos Mapping.

A Novel Hybrid Secure Image Encryption Based on Julia Set of Fractals and 3D Lorenz Chaotic Map (2020)
Journal Article
Masood, F., Ahmad, J., Shah, S. A., Jamal, S. S., & Hussain, I. (2020). A Novel Hybrid Secure Image Encryption Based on Julia Set of Fractals and 3D Lorenz Chaotic Map. Entropy, 22(3), Article 274. https://doi.org/10.3390/e22030274

Chaos-based encryption schemes have attracted many researchers around the world in the digital image security domain. Digital images can be secured using existing chaotic maps, multiple chaotic maps, and several other hybrid dynamic systems that enha... Read More about A Novel Hybrid Secure Image Encryption Based on Julia Set of Fractals and 3D Lorenz Chaotic Map.

Height Prediction for Growth Hormone Deficiency Treatment Planning Using Deep Learning (2020)
Presentation / Conference Contribution
Ilyas, M., Ahmad, J., Lawson, A., Khan, J. S., Tahir, A., Adeel, A., …Hussain, A. (2020). Height Prediction for Growth Hormone Deficiency Treatment Planning Using Deep Learning. In Advances in Brain Inspired Cognitive Systems (76-85). https://doi.org/1

Prospective studies using longitudinal patient data can be used to help to predict responsiveness to Growth Hormone (GH) therapy and assess any suspected risks. In this paper, a novel Clinical Decision Support System (CDSS) is developed to predict gr... Read More about Height Prediction for Growth Hormone Deficiency Treatment Planning Using Deep Learning.

An authentication protocol based on chaos and zero knowledge proof (2020)
Journal Article
Major, W., Buchanan, W. J., & Ahmad, J. (2020). An authentication protocol based on chaos and zero knowledge proof. Nonlinear Dynamics, 99, 3065-3087. https://doi.org/10.1007/s11071-020-05463-3

Port Knocking is a method for authenticating clients through a closed stance firewall, and authorising their requested actions, enabling severs to offer services to authenticated clients, without opening ports on the firewall. Advances in port knocki... Read More about An authentication protocol based on chaos and zero knowledge proof.

WiFreeze: Multiresolution Scalograms for Freezing of Gait Detection in Parkinson's Leveraging 5G Spectrum with Deep Learning (2019)
Journal Article
Tahir, A., Ahmad, J., Shah, S. A., Morison, G., Skelton, D. A., Larijani, H., …Gibson, R. M. (2019). WiFreeze: Multiresolution Scalograms for Freezing of Gait Detection in Parkinson's Leveraging 5G Spectrum with Deep Learning. Electronics, 8(12), https:

Freezing of Gait (FOG) is an episodic absence of forward movement in Parkinson's Disease (PD) patients and represents an onset of disabilities. FOG hinders daily activities and increases fall risk. There is high demand for automating the process of F... Read More about WiFreeze: Multiresolution Scalograms for Freezing of Gait Detection in Parkinson's Leveraging 5G Spectrum with Deep Learning.

A Secure and Robust Image Hashing Scheme Using Gaussian Pyramids (2019)
Journal Article
Bashir, I., Ahmed, F., Ahmad, J., Boulila, W., & Alharbi, N. (2019). A Secure and Robust Image Hashing Scheme Using Gaussian Pyramids. Entropy, 21(11), Article 1132. https://doi.org/10.3390/e21111132

Image hash is an alternative to cryptographic hash functions for checking integrity of digital images. Compared to cryptographic hash functions, an image hash or a Perceptual Hash Function (PHF) is resilient to content preserving distortions and sens... Read More about A Secure and Robust Image Hashing Scheme Using Gaussian Pyramids.

A Novel Real-Time, Lightweight Chaotic-Encryption Scheme for Next-Generation Audio-Visual Hearing Aids (2019)
Journal Article
Adeel, A., Ahmad, J., Larijani, H., & Hussain, A. (2020). A Novel Real-Time, Lightweight Chaotic-Encryption Scheme for Next-Generation Audio-Visual Hearing Aids. Cognitive Computation, 12, 589-601. https://doi.org/10.1007/s12559-019-09653-z

Next-generation audio-visual (AV) hearing aids stand as a major enabler to realize more intelligible audio. However, high data rate, low latency, low computational complexity, and privacy are some of the major bottlenecks to the successful deployment... Read More about A Novel Real-Time, Lightweight Chaotic-Encryption Scheme for Next-Generation Audio-Visual Hearing Aids.

DNA key based visual chaotic image encryption (2019)
Journal Article
Khan, J. S., Ahmad, J., Ahmed, S. S., Siddiqa, H. A., Abbasi, S. F., & Kayhan, S. K. (2019). DNA key based visual chaotic image encryption. Journal of Intelligent and Fuzzy Systems, 37(2), 2549-2561. https://doi.org/10.3233/jifs-182778

With the exponential growth of Internet technologies, digital information exchanged over the Internet is also significantly increased. In order to ensure the security of multimedia contents over the open natured Internet, data should be encrypted. In... Read More about DNA key based visual chaotic image encryption.

HRNN4F: Hybrid deep random neural network for multi-channel fall activity detection (2019)
Journal Article
Tahir, A., Ahmad, J., Morison, G., Larijani, H., Gibson, R. M., & Skelton, D. A. (2019). HRNN4F: Hybrid deep random neural network for multi-channel fall activity detection. Probability in the Engineering and Informational Sciences, 1-14. https://doi.org/

Falls are a major health concern in older adults. Falls lead to mortality, immobility and high costs to social and health care services. Early detection and classification of falls is imperative for timely and appropriate medical aid response. Tradit... Read More about HRNN4F: Hybrid deep random neural network for multi-channel fall activity detection.

RNN-ABC: A New Swarm Optimization Based Technique for Anomaly Detection (2019)
Journal Article
Qureshi, A., Larijani, H., Mtetwa, N., Javed, A., & Ahmad, J. (2019). RNN-ABC: A New Swarm Optimization Based Technique for Anomaly Detection. Computers, 8(3), Article 59. https://doi.org/10.3390/computers8030059

The exponential growth of internet communications and increasing dependency of users upon software-based systems for most essential, everyday applications has raised the importance of network security. As attacks are on the rise, cybersecurity should... Read More about RNN-ABC: A New Swarm Optimization Based Technique for Anomaly Detection.

A Heuristic Intrusion Detection System for Internet-of-Things (IoT) (2019)
Presentation / Conference Contribution
Qureshi, A., Larijani, H., Ahmad, J., & Mtetwa, N. (2019, July). A Heuristic Intrusion Detection System for Internet-of-Things (IoT). Presented at 2019 Computing Conference, London, UK

Today, digitally connected devices are involved in every aspect of life due to the advancements in Internet-of-Things (IoT) paradigm. Recently, it has been a driving force for a major technological revolution towards the development of advanced moder... Read More about A Heuristic Intrusion Detection System for Internet-of-Things (IoT).

Occupancy detection in non-residential buildings – A survey and novel privacy preserved occupancy monitoring solution (2018)
Journal Article
Ahmad, J., Larijani, H., Emmanuel, R., Mannion, M., & Javed, A. (2018). Occupancy detection in non-residential buildings – A survey and novel privacy preserved occupancy monitoring solution. Applied Computing and Informatics, https://doi.org/10.1016/j.a

Buildings use approximately 40% of global energy and are responsible for almost a third of the worldwide greenhouse gas emissions. They also utilise about 60% of the world’s electricity. In the last decade, stringent building regulations have led to... Read More about Occupancy detection in non-residential buildings – A survey and novel privacy preserved occupancy monitoring solution.

An Intelligent Real-Time Occupancy Monitoring System Using Single Overhead Camera (2018)
Presentation / Conference Contribution
Ahmad, J., Larijani, H., Emmanuel, R., Mannion, M., & Javed, A. (2018, September). An Intelligent Real-Time Occupancy Monitoring System Using Single Overhead Camera. Presented at SAI Intelligent Systems Conference, London

Real-time occupancy monitoring information is an important component in building energy management and security. Advances in technology enables us to develop vision-based systems. These systems have gained popularity among different scientific resear... Read More about An Intelligent Real-Time Occupancy Monitoring System Using Single Overhead Camera.

Visual Meaningful Encryption Scheme Using Intertwinning Logistic Map (2018)
Presentation / Conference Contribution
Abbasi, S. F., Ahmad, J., Khan, J. S., Khan, M. A., & Sheikh, S. A. (2019). Visual Meaningful Encryption Scheme Using Intertwinning Logistic Map. . https://doi.org/10.1007/978-3-030-01177-2_56

Transmission of images over the Internet is exponentially increased in the last decade. However, Internet is considered as an insecure channel and hence may cause serious privacy issues. To overcome such privacy concerns, researchers are trying to se... Read More about Visual Meaningful Encryption Scheme Using Intertwinning Logistic Map.

A Novel Random Neural Network Based Approach for Intrusion Detection Systems (2018)
Presentation / Conference Contribution
Qureshi, A., Larijani, H., Ahmad, J., & Mtetwa, N. (2018). A Novel Random Neural Network Based Approach for Intrusion Detection Systems. . https://doi.org/10.1109/ceec.2018.8674228

Computer security and privacy of user specific data is a prime concern in day to day communication. The mass use of internet connected systems has given rise to many vulnerabilities which includes attacks on smart devices. Regular occurrence of such... Read More about A Novel Random Neural Network Based Approach for Intrusion Detection Systems.

DNA Sequence Based Medical Image Encryption Scheme (2018)
Presentation / Conference Contribution
Khan, J. S., Ahmad, J., Abbasi, S. F., Ali, A., & Kayhan, S. K. (2018). DNA Sequence Based Medical Image Encryption Scheme. In 2018 10th Computer Science and Electronic Engineering (CEEC). https://doi.org/10.1109/ceec.2018.8674221

Medical consultants and doctors store and update patients confidential information on Internet cloud computing platforms. These days, securing medical images from eavesdroppers is one of the most challenging and significant research areas. Due to var... Read More about DNA Sequence Based Medical Image Encryption Scheme.

Intertwining and NCA Maps Based New Image Encryption Scheme (2018)
Presentation / Conference Contribution
Khan, F. A., Ahmed, J., Ahmad, J., Khan, J. S., & Stankovic, V. (2018). Intertwining and NCA Maps Based New Image Encryption Scheme. In 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE). https://doi.org/10.1109

In this digital era, the Internet is a main source of communication. Due to exponential advancement in Internet technologies, transmission of multimedia data is very common now. However, transmitting sensitive information over the Internet is always... Read More about Intertwining and NCA Maps Based New Image Encryption Scheme.

Chaos based efficient selective image encryption (2018)
Journal Article
Khan, J. S., & Ahmad, J. (2019). Chaos based efficient selective image encryption. Multidimensional Systems and Signal Processing, 30(2), 943-961. https://doi.org/10.1007/s11045-018-0589-x

Due to social networks, demand for sharing multimedia data is significantly increased in last decade. However, lower complexity and frequent security breaches on public network such as Internet make it easy for eavesdroppers to approach the actual co... Read More about Chaos based efficient selective image encryption.

Detection and prevention of Black Hole Attacks in IOT & WSN (2018)
Presentation / Conference Contribution
Ali, S., Khan, M. A., Ahmad, J., Malik, A. W., & ur Rehman, A. (2018). Detection and prevention of Black Hole Attacks in IOT & WSN. In 2018 Third International Conference on Fog and Mobile Edge Computing (FMEC). https://doi.org/10.1109/fmec.2018.8364068

Wireless Sensor Network is the combination of small devices called sensor nodes, gateways and software. These nodes use wireless medium for transmission and are capable to sense and transmit the data to other nodes. Generally, WSN composed of two typ... Read More about Detection and prevention of Black Hole Attacks in IOT & WSN.

A novel image encryption based on Lorenz equation, Gingerbreadman chaotic map and S8 permutation (2017)
Journal Article
Khan, F. A., Ahmed, J., Khan, J. S., Ahmad, J., & Khan, M. A. (2017). A novel image encryption based on Lorenz equation, Gingerbreadman chaotic map and S8 permutation. Journal of Intelligent and Fuzzy Systems, 33(6), 3753-3765. https://doi.org/10.3233/JIF

Internet is used as the main source of communication throughout the world. However due to public nature of internet data are always exposed to different types of attacks. To address this issue many researchers are working in this area and proposing d... Read More about A novel image encryption based on Lorenz equation, Gingerbreadman chaotic map and S8 permutation.

A new technique for designing 8 × 8 substitution box for image encryption applications (2017)
Presentation / Conference Contribution
Khan, F. A., Ahmed, J., Khan, J. S., Ahmad, J., Khan, M. A., & Hwang, S. O. (2017). A new technique for designing 8 × 8 substitution box for image encryption applications. In 2017 9th Computer Science and Electronic Engineering (CEEC). https://doi.org/1

To create confusion in ciphertexts, encryption processes depends upon nonlinear mappings. This nonlinear mapping can be achieved by a process known as substitution. In a secure encryption algorithm, substitution plays a key role during confusion stag... Read More about A new technique for designing 8 × 8 substitution box for image encryption applications.

A novel substitution box for encryption based on Lorenz equations (2017)
Presentation / Conference Contribution
Khan, F. A., Ahmed, J., Khan, J. S., Ahmad, J., & Khan, M. A. (2017). A novel substitution box for encryption based on Lorenz equations. In 2017 International Conference on Circuits, System and Simulation (ICCSS). https://doi.org/10.1109/cirsyssim.2017.8

Complexity of an encryption algorithm is highly dependent on nonlinear components that drive actual security. Only nonlinear component in all traditional encryption algorithms is mainly Substitution Box (S-Box). In block ciphers, the relationship bet... Read More about A novel substitution box for encryption based on Lorenz equations.

Energy demand prediction through novel random neural network predictor for large non-domestic buildings (2017)
Presentation / Conference Contribution
Ahmad, J., Larijani, H., Emmanuel, R., Mannion, M., Javed, A., & Phillipson, M. (2017). Energy demand prediction through novel random neural network predictor for large non-domestic buildings. In 2017 Annual IEEE International Systems Conference (SysCon)

Buildings are among the largest consumers of energy in the world. In developed countries, buildings currently consumes 40% of the total energy and 51% of total electricity consumption. Energy prediction is a key factor in reducing energy wastage. Thi... Read More about Energy demand prediction through novel random neural network predictor for large non-domestic buildings.

Secure speech communication algorithm via DCT and TD-ERCS chaotic map (2017)
Presentation / Conference Contribution
Habib, Z., Khan, J. S., Ahmad, J., Khan, M. A., & Khan, F. A. (2017). Secure speech communication algorithm via DCT and TD-ERCS chaotic map. In 2017 4th International Conference on Electrical and Electronic Engineering (ICEEE). https://doi.org/10.1109/ic

Secure communication has always been a demanding area in civil, commercial and particularly in military set up. Robust and time-tested efficient algorithms are needed to have an essential privacy for speech transmission in the telephone networks, rad... Read More about Secure speech communication algorithm via DCT and TD-ERCS chaotic map.

A novel image encryption scheme based on orthogonal matrix, skew tent map, and XOR operation (2017)
Journal Article
Ahmad, J., Khan, M. A., Ahmed, F., & Khan, J. S. (2018). A novel image encryption scheme based on orthogonal matrix, skew tent map, and XOR operation. Neural Computing and Applications, 30(12), 3847-3857. https://doi.org/10.1007/s00521-017-2970-3

Content protection is considered as an important issue in today’s world. Therefore, encryption of such contents is a challenging task for researchers. They are focusing on protection of valuable data such as image, video, and audio against different... Read More about A novel image encryption scheme based on orthogonal matrix, skew tent map, and XOR operation.

An efficient and secure partial image encryption for wireless multimedia sensor networks using discrete wavelet transform, chaotic maps and substitution box (2016)
Journal Article
Khan, M. A., Ahmad, J., Javaid, Q., & Saqib, N. A. (2017). An efficient and secure partial image encryption for wireless multimedia sensor networks using discrete wavelet transform, chaotic maps and substitution box. Journal of Modern Optics, 64(5), 531-5

Wireless Sensor Networks (WSN) is widely deployed in monitoring of some physical activity and/or environmental conditions. Data gathered from WSN is transmitted via network to a central location for further processing. Numerous applications of WSN ca... Read More about An efficient and secure partial image encryption for wireless multimedia sensor networks using discrete wavelet transform, chaotic maps and substitution box.

TD-ERCS map-based confusion and diffusion of autocorrelated data (2016)
Journal Article
Khan, J. S., Ahmad, J., & Khan, M. A. (2017). TD-ERCS map-based confusion and diffusion of autocorrelated data. Nonlinear Dynamics, 87(1), 93-107. https://doi.org/10.1007/s11071-016-3028-2

In this article, we proposed a new scheme to encrypt highly autocorrelated image pixel data. In existing literature, single substitution was used to break autocorrelation in images. To get better results, instead of single substitution box, some rese... Read More about TD-ERCS map-based confusion and diffusion of autocorrelated data.

A compression sensing and noise-tolerant image encryption scheme based on chaotic maps and orthogonal matrices (2016)
Journal Article
Ahmad, J., Khan, M. A., Hwang, S. O., & Khan, J. S. (2016). A compression sensing and noise-tolerant image encryption scheme based on chaotic maps and orthogonal matrices. Neural Computing and Applications, 28(S1), 953-967. https://doi.org/10.1007/s00521-

With the evolution of technologies, the size of an image data has been significantly increased. However, traditional image encryption schemes cannot handle the emerging problems in big data such as noise toleration and compression. In order to meet t... Read More about A compression sensing and noise-tolerant image encryption scheme based on chaotic maps and orthogonal matrices.

A New Image Encryption Scheme Based on Dynamic S-Boxes and Chaotic Maps (2016)
Journal Article
Rehman, A. U., Khan, J. S., Ahmad, J., & Hwang, S. O. (2016). A New Image Encryption Scheme Based on Dynamic S-Boxes and Chaotic Maps. 3D research, 7(1), https://doi.org/10.1007/s13319-016-0084-9

Substitution box is a unique and nonlinear core component of block ciphers. A better designing technique of substitution box can boost up the quality of ciphertexts. In this paper, a new encryption method based on dynamic substitution boxes is propos... Read More about A New Image Encryption Scheme Based on Dynamic S-Boxes and Chaotic Maps.

A new chaos-based secure image encryption scheme using multiple substitution boxes (2015)
Presentation / Conference Contribution
Khan, J. S., ur Rehman, A., Ahmad, J., & Habib, Z. (2015). A new chaos-based secure image encryption scheme using multiple substitution boxes. In 2015 Conference on Information Assurance and Cyber Security (CIACS). https://doi.org/10.1109/ciacs.2015.7395

Due to development in Internet and networking technology, multimedia data is broadly transmitted via wired and wireless medium. Thus security is a major concern in modern communication systems. Encryption is one of the pre-eminent ways to guarantee s... Read More about A new chaos-based secure image encryption scheme using multiple substitution boxes.

A secure image encryption scheme based on chaotic maps and affine transformation (2015)
Journal Article
Ahmad, J., & Hwang, S. O. (2016). A secure image encryption scheme based on chaotic maps and affine transformation. Multimedia Tools and Applications, 75(21), 13951-13976. https://doi.org/10.1007/s11042-015-2973-y

Due to the interesting nonlinear dynamic properties of chaotic maps, recently chaos-based encryption algorithms have gained much attention in cryptographic communities. However, many encryption schemes do not fulfil the minimum key space requirement,... Read More about A secure image encryption scheme based on chaotic maps and affine transformation.

Chaos-based diffusion for highly autocorrelated data in encryption algorithms (2015)
Journal Article
Ahmad, J., & Hwang, S. O. (2015). Chaos-based diffusion for highly autocorrelated data in encryption algorithms. Nonlinear Dynamics, 82(4), 1839-1850. https://doi.org/10.1007/s11071-015-2281-0

In a single substitution box, the same regions (pixels) of an image are encrypted to one unique symbol. To reduce this type of autocorrelation in data, chaos has been extensively applied over the last decade. By using chaotic maps, a single substitut... Read More about Chaos-based diffusion for highly autocorrelated data in encryption algorithms.

An efficient image encryption scheme based on: Henon map, skew tent map and S-Box (2015)
Presentation / Conference Contribution
Khan, J., Ahmad, J., & Hwang, S. O. (2015). An efficient image encryption scheme based on: Henon map, skew tent map and S-Box. In 2015 6th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO). https://doi.org/10.1109/ICMSAO

Due to easy and simple implementation, normally single 1-D chaotic maps like logistic and sine maps are employed in multimedia data encryption. However, data encrypted through a single chaotic map does not provide better security in terms of resistan... Read More about An efficient image encryption scheme based on: Henon map, skew tent map and S-Box.

An Experimental Comparison of Chaotic and Non-chaotic Image Encryption Schemes (2015)
Journal Article
Ahmad, J., Hwang, S. O., & Ali, A. (2015). An Experimental Comparison of Chaotic and Non-chaotic Image Encryption Schemes. Wireless Personal Communications, 84(2), 901-918. https://doi.org/10.1007/s11277-015-2667-9

During last few years, transmission of digital multimedia data (images, audios and videos) over Internet, wireless cell phones, television broadcasting etc., has been significantly evolved. The provision of security to store and transmit data with co... Read More about An Experimental Comparison of Chaotic and Non-chaotic Image Encryption Schemes.

Comparative analysis of chaotic and non-chaotic image encryption schemes (2014)
Presentation / Conference Contribution
Younas, M. B., & Ahmad, J. (2014). Comparative analysis of chaotic and non-chaotic image encryption schemes. In 2014 International Conference on Emerging Technologies (ICET). https://doi.org/10.1109/icet.2014.7021021

In modern era, multimedia technologies have been developed significantly. Multimedia data such as audio, video and image transfers over the internet is open and insecure. Security is required for storage and transmission of digital images to avoid fr... Read More about Comparative analysis of chaotic and non-chaotic image encryption schemes.