Skip to main content

Research Repository

Advanced Search

Outputs (164)

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.

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.