All Outputs (154)

A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos-Based Quantum Map (2022)
Journal Article
Alharbi, A. R., Ahmad, J., Arshad, Shaukat, S., Masood, F., Ghadi, Y. Y., Pitropakis, N., & Buchanan, W. J. (2022). A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos-Based Quantum Map. Complexity, 2022, Article 7047282. https://doi.org/10.1155/2022/7047282

With the increasing volume of data transmission through insecure communication channels, big data security has become one of the important concerns in the cybersecurity domain. To address these concerns and keep data safe, a robust privacy-preserving... Read More about A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos-Based Quantum Map.

Optimal Pitch Angle Controller for DFIG-Based Wind Turbine System Using Computational Optimization Techniques (2022)
Journal Article
Khurshid, A., Mughal, M. A., Othman, A., Al-Hadhrami, T., Kumar, H., Khurshid, I., Arshad, & Ahmad, J. (2022). Optimal Pitch Angle Controller for DFIG-Based Wind Turbine System Using Computational Optimization Techniques. Electronics, 11(8), Article 1290. https://doi.org/10.3390/electronics11081290

With the advent of high-speed and parallel computing, the applicability of computational optimization in engineering problems has increased, with greater validation than conventional methods. Pitch angle is an effective variable in extracting maximum... Read More about Optimal Pitch Angle Controller for DFIG-Based Wind Turbine System Using Computational Optimization Techniques.

A novel image encryption scheme based on Arnold cat map, Newton-Leipnik system and Logistic Gaussian map (2022)
Journal Article
Masood, F., Boulila, W., Alsaeedi, A., Khan, J. S., Ahmad, J., Khan, M. A., & Rehman, S. U. (2022). A novel image encryption scheme based on Arnold cat map, Newton-Leipnik system and Logistic Gaussian map. Multimedia Tools and Applications, 81, 30931-30959. https://doi.org/10.1007/s11042-022-12844-w

In the existing literature, numerous chaos-based multimedia encryption schemes have been presented. Benefiting from inherent properties such as ergodicity and key-sensitivity; this can potentially improve non-linearity in encrypted data. This paper i... Read More about A novel image encryption scheme based on Arnold cat map, Newton-Leipnik system and Logistic Gaussian map.

A federated learning framework for cyberattack detection in vehicular sensor networks (2022)
Journal Article
Driss, M., Almomani, I., e Huma, Z., & Ahmad, J. (2022). A federated learning framework for cyberattack detection in vehicular sensor networks. Complex and Intelligent Systems, 8(5), 4221-4235. https://doi.org/10.1007/s40747-022-00705-w

Vehicular Sensor Networks (VSN) introduced a new paradigm for modern transportation systems by improving traffic management and comfort. However, the increasing adoption of smart sensing technologies with the Internet of Things (IoT) made VSN a high-... Read More about A federated learning framework for cyberattack detection in vehicular sensor networks.

A Smart and Robust Automatic Inspection of Printed Labels Using an Image Hashing Technique (2022)
Journal Article
Khan, M. A., Ahmed, F., Khan, M. D., Ahmad, J., Kumar, H., & Pitropakis, N. (2022). A Smart and Robust Automatic Inspection of Printed Labels Using an Image Hashing Technique. Electronics, 11(6), Article 955. https://doi.org/10.3390/electronics11060955

This work is focused on the development of a smart and automatic inspection system for printed labels. This is a challenging problem to solve since the collected labels are typically subjected to a variety of geometric and non-geometric distortions.... Read More about A Smart and Robust Automatic Inspection of Printed Labels Using an Image Hashing Technique.

Dynamic S-Box and PWLCM-Based Robust Watermarking Scheme (2022)
Journal Article
Sher Khan, J., Koç Kayhan, S., Siddiq Ahmed, S., Ahmad, J., Ayesha Siddiqa, H., Ahmed, F., Ghaleb, B., & Al Dubai, A. (2022). Dynamic S-Box and PWLCM-Based Robust Watermarking Scheme. Wireless Personal Communications, 125, 513-530. https://doi.org/10.1007/s11277-022-09562-9

Due to the increased number of cyberattacks, numerous researchers are motivated towards the design of such schemes that can hide digital information in a signal. Watermarking is one of the promising technologies that can protect digital information.... Read More about Dynamic S-Box and PWLCM-Based Robust Watermarking Scheme.

Evolution towards Smart and Software-Defined Internet of Things (2022)
Journal Article
Abid, M. A., Afaqui, N., Khan, M. A., Akhtar, M. W., Malik, A. W., Munir, A., …Shabir, B. (2022). Evolution towards Smart and Software-Defined Internet of Things. AI, 3(1), 100-123. https://doi.org/10.3390/ai3010007

The Internet of Things (IoT) is a mesh network of interconnected objects with unique identifiers that can transmit data and communicate with one another without the need for human intervention. The IoT has brought the future closer to us. It has open... Read More about Evolution towards Smart and Software-Defined Internet of Things.

Detecting Alzheimer’s Disease Using Machine Learning Methods (2022)
Presentation / Conference Contribution
Dashtipour, K., Taylor, W., Ansari, S., Zahid, A., Gogate, M., Ahmad, J., Assaleh, K., Arshad, K., Ali Imran, M., & Abbasi, Q. (2021, October). Detecting Alzheimer’s Disease Using Machine Learning Methods. Presented at 16th EAI International Conference, BODYNETS 2021, Online

As the world is experiencing population growth, the portion of the older people, aged 65 and above, is also growing at a faster rate. As a result, the dementia with Alzheimer’s disease is expected to increase rapidly in the next few years. Currently,... Read More about Detecting Alzheimer’s Disease Using Machine Learning Methods.

Comparing the Performance of Different Classifiers for Posture Detection (2022)
Presentation / Conference Contribution
Suresh Kumar, S., Dashtipour, K., Gogate, M., Ahmad, J., Assaleh, K., Arshad, K., Imran, M. A., Abbasi, Q., & Ahmad, W. (2021, October). Comparing the Performance of Different Classifiers for Posture Detection. Presented at 16th EAI International Conference, BODYNETS 2021, Online

Human Posture Classification (HPC) is used in many fields such as human computer interfacing, security surveillance, rehabilitation, remote monitoring, and so on. This paper compares the performance of different classifiers in the detection of 3 post... Read More about Comparing the Performance of Different Classifiers for Posture Detection.

HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles (2022)
Journal Article
Ullah, S., Khan, M. A., Ahmad, J., Jamal, S. S., e Huma, Z., Hassan, M. T., Pitropakis, N., Arshad, & Buchanan, W. J. (2022). HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles. Sensors, 22(4), Article 1340. https://doi.org/10.3390/s22041340

Internet of Vehicles (IoV) is an application of the Internet of Things (IoT) network that connects smart vehicles to the internet, and vehicles with each other. With the emergence of IoV technology, customers have placed great attention on smart vehi... Read More about HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles.

Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers (2022)
Presentation / Conference Contribution
Ali, H., Papadopoulos, P., Ahmad, J., Pit, N., Jaroucheh, Z., & Buchanan, W. J. (2021, December). Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers. Presented at IEEE SINCONF: 14th International Conference on Security of Information and Networks, Edinburgh

Threat information sharing is considered as one of the proactive defensive approaches for enhancing the overall security of trusted partners. Trusted partner organizations can provide access to past and current cybersecurity threats for reducing the... Read More about Privacy-preserving and Trusted Threat Intelligence Sharing using Distributed Ledgers.

Chest X-ray Classification for the Detection of COVID-19 Using Deep Learning Techniques (2022)
Journal Article
Khan, E., Rehman, M. Z. U., Ahmed, F., Alfouzan, F. A., Alzahrani, N. M., & Ahmad, J. (2022). Chest X-ray Classification for the Detection of COVID-19 Using Deep Learning Techniques. Sensors, 22(3), Article 1211. https://doi.org/10.3390/s22031211

Recent technological developments pave the path for deep learning-based techniques to be used in almost every domain of life. The precision of deep learning techniques make it possible for these to be used in the medical field for the classification... Read More about Chest X-ray Classification for the Detection of COVID-19 Using Deep Learning Techniques.

Semantic Segmentation and Edge Detection—Approach to Road Detection in Very High Resolution Satellite Images (2022)
Journal Article
Ghandorh, H., Boulila, W., Masood, S., Koubaa, A., Ahmed, F., & Ahmad, J. (2022). Semantic Segmentation and Edge Detection—Approach to Road Detection in Very High Resolution Satellite Images. Remote Sensing, 14(3), Article 613. https://doi.org/10.3390/rs14030613

Road detection technology plays an essential role in a variety of applications, such as urban planning, map updating, traffic monitoring and automatic vehicle navigation. Recently, there has been much development in detecting roads in high-resolution... Read More about Semantic Segmentation and Edge Detection—Approach to Road Detection in Very High Resolution Satellite Images.

Ransomware: Analysing the Impact on Windows Active Directory Domain Services (2022)
Journal Article
McDonald, G., Papadopoulos, P., Pitropakis, N., Ahmad, J., & Buchanan, W. J. (2022). Ransomware: Analysing the Impact on Windows Active Directory Domain Services. Sensors, 22(3), Article 953. https://doi.org/10.3390/s22030953

Ransomware has become an increasingly popular type of malware across the past decade and continues to rise in popularity due to its high profitability. Organisations and enterprises have become prime targets for ransomware as they are more likely to... Read More about Ransomware: Analysing the Impact on Windows Active Directory Domain Services.

A Novel Chaotic Permutation-Substitution Image Encryption Scheme Based on Logistic Map and Random Substitution (2022)
Journal Article
Arif, J., Khan, M. A., Ghaleb, B., Ahmad, J., Munir, A., Rashid, U., & Al-Dubai, A. Y. (2022). A Novel Chaotic Permutation-Substitution Image Encryption Scheme Based on Logistic Map and Random Substitution. IEEE Access, 10, 12966-12982. https://doi.org/10.1109/access.2022.3146792

Privacy is a serious concern related to sharing videos or images among people over the Internet. As a method to preserve images’ privacy, chaos-based image encryption algorithms have been used widely to fulfil such a requirement. However, these algor... Read More about A Novel Chaotic Permutation-Substitution Image Encryption Scheme Based on Logistic Map and Random Substitution.

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), Article 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), Article 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.

Novel Privacy Preserving Non-Invasive Sensing-Based Diagnoses of Pneumonia Disease Leveraging Deep Network Model (2022)
Journal Article
Rehman, M. U., Shafique, A., Khan, K. H., Khalid, S., Alotaibi, A. A., Althobaiti, T., Ramzan, N., Ahmad, J., Shah, S. A., & Abbasi, Q. H. (2022). Novel Privacy Preserving Non-Invasive Sensing-Based Diagnoses of Pneumonia Disease Leveraging Deep Network Model. Sensors, 22(2), Article 461. https://doi.org/10.3390/s22020461

This article presents non-invasive sensing-based diagnoses of pneumonia disease, exploiting a deep learning model to make the technique non-invasive coupled with security preservation. Sensing and securing healthcare and medical images such as X-rays... Read More about Novel Privacy Preserving Non-Invasive Sensing-Based Diagnoses of Pneumonia Disease Leveraging Deep Network Model.

Machine learning empowered COVID-19 patient monitoring using non-contact sensing: An extensive review (2022)
Journal Article
Saeed, U., Shah, S. Y., Ahmad, J., Imran, M. A., Abbasi, Q. H., & Shah, S. A. (2022). Machine learning empowered COVID-19 patient monitoring using non-contact sensing: An extensive review. Journal of Pharmaceutical Analysis, 12(2), 193-204. https://doi.org/10.1016/j.jpha.2021.12.006

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which caused the coronavirus disease 2019 (COVID-19) pandemic, has affected more than 400 million people worldwide. With the recent rise of new Delta and Omicron variants, the efficacy... Read More about Machine learning empowered COVID-19 patient monitoring using non-contact sensing: An extensive review.

Browsers’ Private Mode: Is It What We Were Promised? (2021)
Journal Article
Hughes, K., Papadopoulos, P., Pitropakis, N., Smales, A., Ahmad, J., & Buchanan, W. J. (2021). Browsers’ Private Mode: Is It What We Were Promised?. Computers, 10(12), Article 165. https://doi.org/10.3390/computers10120165

Web browsers are one of the most used applications on every computational device in our days. Hence, they play a pivotal role in any forensic investigation and help determine if nefarious or suspicious activity has occurred on that device. Our study... Read More about Browsers’ Private Mode: Is It What We Were Promised?.