Dr Jawad Ahmad's Outputs (25)

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.

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., Qadri, M. T., & Ahmad, J. (2023). Privacy-Enhanced Pneumonia Diagnosis: IoT-Enabled Federated Multi-Party Computation in Industry 5.0. IEEE Transactions on Consumer Electronics, 70(1), 1923-1939. https://doi.org/10.1109/tce.2023.3319565

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.

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.

Resolving the Decreased Rank Attack in RPL’s IoT Networks (2023)
Presentation / Conference Contribution
Ghaleb, B., Al-Dubai, A., Hussain, A., Ahmad, J., Romdhani, I., & Jaroucheh, Z. (2023, June). Resolving the Decreased Rank Attack in RPL’s IoT Networks. Presented at 19th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT 2023), Pafos, Cyprus

The Routing Protocol for Low power and Lossy networks (RPL) has been developed by the Internet Engineering Task Force (IETF) standardization body to serve as a part of the 6LoWPAN (IPv6 over Low-Power Wireless Personal Area Networks) standard, a core... Read More about Resolving the Decreased Rank Attack in RPL’s IoT Networks.

Advanced Sensing Techniques for Intelligent Human Activity Recognition Using Machine Learning (2023)
Journal Article
Shah, S. A., Abbasi, Q. H., Ahmad, J., & Imran, M. A. (2023). Advanced Sensing Techniques for Intelligent Human Activity Recognition Using Machine Learning. Electronics, 12(19), Article 3990. https://doi.org/10.3390/electronics12193990

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., Alsulami, M., Alshehri, M. S., Ghadi, Y. Y., & 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.org/10.1186/s42408-023-00216-0

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., Hameed, H., & 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), 22111-22118. https://doi.org/10.1109/jsen.2023.3308972

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.

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., Arshad, Abbasi, Q. H., & Ahmad, J. (2022, October). A Comparison of Ensemble Learning for Intrusion Detection in Telemetry Data. Presented at 3rd International Conference of Advanced Computing and Informatics, Casablanca, Morocco

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.