All Outputs (144)

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, 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.

Enhancing Cloud Computing Security Through Blockchain-Based Communication for Electronic Health Records (2024)
Conference Proceeding
Noyon, M. S. I., Moradpoor, N., Maglaras, L., & Ahmad, J. (in press). Enhancing Cloud Computing Security Through Blockchain-Based Communication for Electronic Health Records.

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.

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., …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/cit2.12292

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.

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.

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.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.

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, 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.

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., …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., …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.