All Outputs (51)

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), 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.

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. (2023). A Comparison of Ensemble Learning for Intrusion Detection in Telemetry Data. Advances on Intelligent Computing and Data Science. ICACIn 2022. (179, pp. 451-462). Springer. https://doi.org/10.1007/978-3-031-36258-3_40

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.

A Hybrid Neuro-Fuzzy Approach for Heterogeneous Patch Encoding in ViTs Using Contrastive Embeddings and Deep Knowledge Dispersion (2023)
Journal Article
Shah, S. M. A. H., Khan, M. Q., Ghadi, Y. Y., Jan, S. U., Mzoughi, O., & Hamdi, M. (2023). A Hybrid Neuro-Fuzzy Approach for Heterogeneous Patch Encoding in ViTs Using Contrastive Embeddings and Deep Knowledge Dispersion. IEEE Access, 11, 83171-83186. https://doi.org/10.1109/access.2023.3302253

Vision Transformers (ViT) are commonly utilized in image recognition and related applications. It delivers impressive results when it is pre-trained using massive volumes of data and then employed in mid-sized or small-scale image recognition evaluat... Read More about A Hybrid Neuro-Fuzzy Approach for Heterogeneous Patch Encoding in ViTs Using Contrastive Embeddings and Deep Knowledge Dispersion.

Wasserstein GAN-based Digital Twin Inspired Model for Early Drift Fault Detection in Wireless Sensor Networks (2023)
Journal Article
Hasan, M. N., Jan, S. U., & Koo, I. (2023). Wasserstein GAN-based Digital Twin Inspired Model for Early Drift Fault Detection in Wireless Sensor Networks. IEEE Sensors Journal, 23(12), 13327-13339. https://doi.org/10.1109/JSEN.2023.3272908

In this Internet of Things (IoT) era, the number of devices capable of sensing their surroundings is increasing day by day. Based on the data from these devices, numerous services and systems are now offered where critical decisions depend on the dat... Read More about Wasserstein GAN-based Digital Twin Inspired Model for Early Drift Fault Detection in Wireless Sensor Networks.

BIoMT: A Blockchain-Enabled Healthcare Architecture for Information Security in the Internet of Medical Things (2023)
Journal Article
Badri, S., Ullah Jan, S., Alghazzawi, D., Aldhaheri, S., & Pitropakis, N. (2023). BIoMT: A Blockchain-Enabled Healthcare Architecture for Information Security in the Internet of Medical Things. Computer Systems Science and Engineering, 46(3), 3667-3684. https://doi.org/10.32604/csse.2023.037531

Rapid technological advancement has enabled modern healthcare systems to provide more sophisticated and real-time services on the Internet of Medical Things (IoMT). The existing cloud-based, centralized IoMT architectures are vulnerable to multiple s... Read More about BIoMT: A Blockchain-Enabled Healthcare Architecture for Information Security in the Internet of Medical Things.

A Systematic and Comprehensive Survey of Recent Advances in Intrusion Detection Systems Using Machine Learning: Deep Learning, Datasets, and Attack Taxonomy (2023)
Journal Article
Momand, A., Jan, S. U., & Ramzan, N. (2023). A Systematic and Comprehensive Survey of Recent Advances in Intrusion Detection Systems Using Machine Learning: Deep Learning, Datasets, and Attack Taxonomy. Journal of Sensors, 2023, 6048087. https://doi.org/10.1155/2023/6048087

Recently, intrusion detection systems (IDS) have become an essential part of most organisations’ security architecture due to the rise in frequency and severity of network attacks. To identify a security breach, the target machine or network must be... Read More about A Systematic and Comprehensive Survey of Recent Advances in Intrusion Detection Systems Using Machine Learning: Deep Learning, Datasets, and Attack Taxonomy.

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., Driss, M., & Ahmad, J. (2022). A Novel Chaos-Based Privacy-Preserving Deep Learning Model for Cancer Diagnosis. IEEE Transactions on Network Science and Engineering, 9(6), 4322-4337. https://doi.org/10.1109/tnse.2022.3199235

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.

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. 2022 2nd International Conference of Smart Systems and Emerging Technologies (SMARTTECH). IEEE. https://doi.org/10.1109/smarttech54121.2022.00016

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.

Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review (2022)
Journal Article
Gulzar Ahmad, S., Iqbal, T., Javaid, A., Ullah Munir, E., Kirn, N., Jan, S. U., & Ramzan, N. (2022). Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review. Sensors, 22(12), 4362. https://doi.org/10.3390/s22124362

Currently, information and communication technology (ICT) allows health institutions to reach disadvantaged groups in rural areas using sensing and artificial intelligence (AI) technologies. Applications of these technologies are even more essential... Read More about Sensing and Artificial Intelligent Maternal-Infant Health Care Systems: A Review.

IoT-Enabled Vehicle Speed Monitoring System (2022)
Journal Article
Khan, S. U., Alam, N., Jan, S. U., & Koo, I. S. (2022). IoT-Enabled Vehicle Speed Monitoring System. Electronics, 11(4), 614. https://doi.org/10.3390/electronics11040614

Millions of people lose their lives each year worldwide due to traffic law violations, specifically, over speeding. The existing systems fail to report most of such violations due to their respective flaws. For instance, speed guns work in isolation... Read More about IoT-Enabled Vehicle Speed Monitoring System.

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., Ramzan, N., Ullah Jan, S., Ahmad, J., & H. Abbasi, Q. (2022). Multiple Participants’ Discrete Activity Recognition in a Well-Controlled Environment Using Universal Software Radio Peripheral Wireless Sensing. Sensors, 22(3), 809. https://doi.org/10.3390/s22030809

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., Ramzan, N., Ullah Jan, S., Ahmad, J., & Abbasi, Q. H. (2022). Multiple Participants’ Discrete Activity Recognition in a Well-Controlled Environment Using Universal Software Radio Peripheral Wireless Sensing. Sensors, 22(3), 809. https://doi.org/10.3390/s22030809

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.

Transfer learning-based method for detection of COVID-19 using X-Ray Images (2021)
Presentation / Conference Contribution
Rehman, A., Tariq, Z., Jan, S. U., Aziz, S., Khan, M. U., & Chaudry, H. N. (2021). Transfer learning-based method for detection of COVID-19 using X-Ray Images. 2021 International Conference on Robotics and Automation in Industry (ICRAI). IEEE. https://doi.org/10.1109/icrai54018.2021.9651463

In this paper, we have performed transfer learning using different pre-trained convolutional neural networks for binary classification of X-ray images into COVID-19 disease and normal. The dataset is gathered from two open sources. Our dataset is con... Read More about Transfer learning-based method for detection of COVID-19 using X-Ray Images.

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, 21(21), 7016. https://doi.org/10.3390/s21217016

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.

A Review and Comparison of the State-of-the-Art Techniques for Atrial Fibrillation Detection and Skin Hydration (2021)
Journal Article
Liaqat, S., Dashtipour, K., Zahid, A., Arshad, K., Ullah Jan, S., Assaleh, K., & Ramzan, N. (2021). A Review and Comparison of the State-of-the-Art Techniques for Atrial Fibrillation Detection and Skin Hydration. Frontiers in Communications and Networks, 2, 679502. https://doi.org/10.3389/frcmn.2021.679502

Atrial fibrillation (AF) is one of the most common types of cardiac arrhythmia, with a prevalence of 1–2% in the community, increasing the risk of stroke and myocardial infarction. Early detection of AF, typically causing an irregular and abnormally... Read More about A Review and Comparison of the State-of-the-Art Techniques for Atrial Fibrillation Detection and Skin Hydration.

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, 1405-1432. https://doi.org/10.1007/s11277-021-08584-z

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.

CAFD: Context-Aware Fault Diagnostic Scheme towards Sensor Faults Utilizing Machine Learning (2021)
Journal Article
Saeed, U., Lee, Y.-D., Jan, S. U., & Koo, I. (2021). CAFD: Context-Aware Fault Diagnostic Scheme towards Sensor Faults Utilizing Machine Learning. Sensors, 21(2), 617. https://doi.org/10.3390/s21020617

Sensors’ existence as a key component of Cyber-Physical Systems makes it susceptible to failures due to complex environments, low-quality production, and aging. When defective, sensors either stop communicating or convey incorrect information. These... Read More about CAFD: Context-Aware Fault Diagnostic Scheme towards Sensor Faults Utilizing Machine Learning.

Fault diagnosis based on extremely randomized trees in wireless sensor networks (2020)
Journal Article
Saeed, U., Jan, S. U., Lee, Y.-D., & Koo, I. (2021). Fault diagnosis based on extremely randomized trees in wireless sensor networks. Reliability Engineering and System Safety, 205, 107284. https://doi.org/10.1016/j.ress.2020.107284

Wireless Sensor Network (WSN) being highly diversified cyber–physical system makes it vulnerable to numerous failures, which can cause devastation towards safety, economy, and systems’ reliability. Precise detection and diagnosis of failures or fault... Read More about Fault diagnosis based on extremely randomized trees in wireless sensor networks.

A distributed sensor-fault detection and diagnosis framework using machine learning (2020)
Journal Article
Jan, S. U., Lee, Y. D., & Koo, I. S. (2021). A distributed sensor-fault detection and diagnosis framework using machine learning. Information Sciences, 547, 777-796. https://doi.org/10.1016/j.ins.2020.08.068

The objective of this work is to design a sensor-fault detection and diagnosis system for the Internet of Things and Cyber-Physical Systems. The challenge is, however, achieving this objective within the limited computation, memory, and energy resour... Read More about A distributed sensor-fault detection and diagnosis framework using machine learning.

Machine Learning-based Real-Time Sensor Drift Fault Detection using Raspberry Pi (2020)
Presentation / Conference Contribution
Saeed, U., Ullah Jan, S., Lee, Y.-D., & Koo, I. (2020). Machine Learning-based Real-Time Sensor Drift Fault Detection using Raspberry Pi. 2020 International Conference on Electronics, Information, and Communication (ICEIC). IEEE. https://doi.org/10.1109/iceic49074.2020.9102342

From smart industries to smart cities, sensors in the modern world plays an important role by covering a large number of applications. However, sensors get faulty sometimes leading to serious outcomes in terms of safety, economic cost and reliability... Read More about Machine Learning-based Real-Time Sensor Drift Fault Detection using Raspberry Pi.