Dr Jawad Ahmad's Outputs (170)

PermutEx: Feature-Extraction-Based Permutation — A New Diffusion Scheme for Image Encryption Algorithms (2024)
Presentation / Conference Contribution
Khan, M. S., Ahmad, J., Al-Dubai, A., Jaroucheh, Z., Pitropakis, N., & Buchanan, W. J. (2023, November). PermutEx: Feature-Extraction-Based Permutation — A New Diffusion Scheme for Image Encryption Algorithms. Presented at 2023 IEEE 28th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Edinburgh, United Kingdom

Traditional permutation schemes mostly focus on random scrambling of pixels, often neglecting the intrinsic image information that could enhance diffusion in image encryption algorithms. This paper introduces PermutEx, a feature-extractionbased permu... Read More about PermutEx: Feature-Extraction-Based Permutation — A New Diffusion Scheme for Image Encryption Algorithms.

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.org/10.1109/access.2024.3371992

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/10.1016/j.eswa.2023.121378

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/10.1109/jsen.2024.3364389

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., Changalasetty, S. B., Alhaisoni, M., & Ahmad, J. (2024). A novel medical image data protection scheme for smart healthcare system. CAAI Transactions on Intelligence Technology, 9(4), 821-836. https://doi.org/10.1049/cit2.12292

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.

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 Conference on Engineering and Emerging Technologies (IEEE ICEET 2023), Istanbul, Turkey

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.

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, Article 101013. https://doi.org/10.1016/j.iot.2023.101013

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.jnca.2023.103784

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.2023.110105

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.

PASSION: Permissioned Access Control for Segmented Devices and Identity for IoT Networks (2023)
Presentation / Conference Contribution
Ali, H., Abubakar, M., Ahmad, J., Buchanan, W. J., & Jaroucheh, Z. (2023, November). PASSION: Permissioned Access Control for Segmented Devices and Identity for IoT Networks. Presented at 2023 IEEE 28th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Edinburgh, United Kingdom

In recent years, there has been a significant proliferation of industrial Internet of Things (IoT) applications, with a wide variety of use cases being developed and put into operation. As the industrial IoT landscape expands, the establishment of se... Read More about PASSION: Permissioned Access Control for Segmented Devices and Identity for IoT Networks.

Noise-Crypt: Image Encryption with Non-linear Noise, Hybrid Chaotic Maps, and Hashing (2023)
Presentation / Conference Contribution
Asghar, L., Ahmed, F., Khan, M. S., Arshad, A., & Ahmad, J. (2023, October). Noise-Crypt: Image Encryption with Non-linear Noise, Hybrid Chaotic Maps, and Hashing. Presented at 2023 International Conference on Engineering and Emerging Technologies (ICEET), Istanbul, Turkiye

To secure the digital images over insecure transmission channels, a new image encryption algorithm Noise-Crypt is proposed in this paper. Noise-Crypt integrates nonlinear random noise, hybrid chaotic maps, and SHA-256 hashing algorithm. The utilized... Read More about Noise-Crypt: Image Encryption with Non-linear Noise, Hybrid Chaotic Maps, and Hashing.

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., Jan, S. U., & 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.org/10.1016/j.comnet.2023.110072

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 Environments (75-98). Springer. https://doi.org/10.1007/978-3-031-47590-0_5

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.

CellSecure: Securing Image Data in Industrial Internet-of-Things via Cellular Automata and Chaos-Based Encryption (2023)
Presentation / Conference Contribution
Ali, H., Khan, M. S., Driss, M., Ahmad, J., Buchanan, W. J., & Pitropakis, N. (2023, October). CellSecure: Securing Image Data in Industrial Internet-of-Things via Cellular Automata and Chaos-Based Encryption. Presented at 2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall), Hong Kong, Hong Kong

In the era of Industrial IoT (IIoT) and Industry 4.0, ensuring secure data transmission has become a critical concern. Among other data types, images are widely transmitted and utilized across various IIoT applications, ranging from sensor-generated... Read More about CellSecure: Securing Image Data in Industrial Internet-of-Things via Cellular Automata and Chaos-Based Encryption.