Jawad Ahmad
jawad ahmad

Dr Jawad Ahmad

Lecturer

 0131 455 3237

  J.Ahmad@napier.ac.uk

  

Biography

Dr Jawad Ahmad (SMIEEE) is a highly experienced teacher with a decade of teaching and research experience in prestigious institutes. He has taught at renowned institutions such as Â鶹ÉçÇø (UK) and Glasgow Caledonian University (UK) etc. He has also served as a supervisor for several PhD, MSc, and undergraduate students, providing guidance and support for their dissertations. He has published in renowned journals including IEEE Transactions, ACM Transactions, Elsevier and Springer with over 150 research papers and 4500 citations. For the past three years, his name has appeared on the list of the world's top 2% scientists in Cybersecurity, as published by Clarivate (a list endorsed by Stanford University, USA). Furthermore, in 2020, he was recognized as a Global Talent in the area of Cybersecurity by the Royal Academy of Engineering (UK). To date, he has secured research and funding grants totalling £195K. In terms of academic achievements, he has earned a Gold medal for his outstanding performance in MSc and a Bronze medal for his achievements in BSc.

School

Research Groups

Esteem

Conference Organising Activity

  • Best Paper Award.
  • Best Paper Award.
  • Track Chair (Cyber Security Track).
  • Session Chair (Artificial Intelligence and Data Science Track).

 

Editorial Activity

  • Guest Editor.

 

Fellowships and Awards

  • Gold Medal Award
  • Bronze Medal Award

 

Reviewing

  • Outstanding Contributions in Reviewing Award

 

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Date


154 results

Privacy-enhanced skin disease classification: integrating federated learning in an IoT-enabled edge computing

Journal Article
Alasbali, N., Ahmad, J., Siddique, A. A., Saidani, O., Al Mazroa, A., Raza, A., Ullah, R., & Khan, M. S. (2025)
Privacy-enhanced skin disease classification: integrating federated learning in an IoT-enabled edge computing. Frontiers in Computer Science, 7, Article 1550677. https://doi.org/10.3389/fcomp.2025.1550677
Introduction: The accurate and timely diagnosis of skin diseases is a critical concern, as many skin diseases exhibit similar symptoms in the early stages. Most existing autom...

Leveraging LLMs for Non-Security Experts in Threat Hunting: Detecting Living off the Land Techniques

Journal Article
Konstantinou, A., Kasimatis, D., Buchanan, W. J., Ullah Jan, S., Ahmad, J., Politis, I., & Pitropakis, N. (2025)
Leveraging LLMs for Non-Security Experts in Threat Hunting: Detecting Living off the Land Techniques. Machine Learning and Knowledge Extraction, 7(2), Article 31. https://doi.org/10.3390/make7020031
This paper explores the potential use of Large Language Models (LLMs), such as ChatGPT, Google Gemini, and Microsoft Copilot, in threat hunting, specifically focusing on Livin...

Enhancing AI-Generated Image Detection with a Novel Approach and Comparative Analysis

Presentation / Conference Contribution
Weir, S., Khan, M. S., Moradpoor, N., & Ahmad, J. (2024, December)
Enhancing AI-Generated Image Detection with a Novel Approach and Comparative Analysis. Presented at 2024 17th International Conference on Security of Information and Networks (SIN), Sydney, Australia
This study explores advancements in AI-generated image detection, emphasizing the increasing realism of images, including deepfakes, and the need for effective detection metho...

Sustainable Environmental Monitoring: Multistage Fusion Algorithm for Remotely Sensed Underwater Super-Resolution Image Enhancement and Classification

Journal Article
Ghaban, W., Ahmad, J., Siddique, A. A., Alshehri, M. S., Saghir, A., Saeed, F., Ghaleb, B., & Rehman, M. U. (2025)
Sustainable Environmental Monitoring: Multistage Fusion Algorithm for Remotely Sensed Underwater Super-Resolution Image Enhancement and Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 18, 3640-3653. https://doi.org/10.1109/jstars.2024.3522202
Oceans and seas cover more than 70% of the Earth's surface. If compared with the land mass there are a lot of unexplored locations, a wealth of natural resources, and diverse ...

A Novel Cosine-Modulated-Polynomial Chaotic Map to Strengthen Image Encryption Algorithms in IoT Environments

Presentation / Conference Contribution
Khan, M. S., Ahmad, J., Al-Dubai, A., Pitropakis, N., Driss, M., & Buchanan, W. J. (2024, September)
A Novel Cosine-Modulated-Polynomial Chaotic Map to Strengthen Image Encryption Algorithms in IoT Environments. Presented at 28th International Conference on Knowledge Based and Intelligent information and Engineering Systems (KES 2024), Spain
With the widespread use of the Internet of Things (IoT), securing the storage and transmission of multimedia content across IoT devices is a critical concern. Chaos-based Pseu...

VisCrypt: Image Encryption Featuring Novel Chaotic Key Generation and Block Permutation Techniques with Visual Cryptography

Presentation / Conference Contribution
Khan, M. S., Ahmad, J., Ali, M., Al Dubai, A., Pitropakis, N., & Buchanan, W. J. (2024, July)
VisCrypt: Image Encryption Featuring Novel Chaotic Key Generation and Block Permutation Techniques with Visual Cryptography. Presented at 2024 IEEE 7th International Conference on Advanced Technologies, Signal and Image Processing (ATSIP), Sousse, Tunisia
In this digital era, ensuring the security of data transmission is critically important. Digital data, especially image data, needs to be secured against unauthorized access. ...

ML-FAS: Multi-Level Face Anonymization Scheme and Its Application to E-Commerce Systems

Journal Article
Jiang, D., Ahmad, J., Suo, Z., Alsulami, M. M., Ghadi, Y. Y., & Boulila, W. (2024)
ML-FAS: Multi-Level Face Anonymization Scheme and Its Application to E-Commerce Systems. IEEE Transactions on Consumer Electronics, 70(3), 5090 - 5100. https://doi.org/10.1109/tce.2024.3411102
With the proliferation of electronic commerce, the facial data used for identity authentication and mobile payment are potentially subject to data analytics and mining attacks...

A transformer-based approach empowered by a self-attention technique for semantic segmentation in remote sensing

Journal Article
Semantic segmentation of Remote Sensing (RS) images involves the classification of each pixel in a satellite image into distinct and non-overlapping regions or segments. This ...

PermutEx: Feature-Extraction-Based Permutation — A New Diffusion Scheme for Image Encryption Algorithms

Presentation / Conference Contribution
Khan, M. S., Ahmad, J., Al-Dubai, A., Jaroucheh, Z., Pitropakis, N., & Buchanan, W. J. (2023, November)
PermutEx: Feature-Extraction-Based Permutation — A New Diffusion Scheme for Image Encryption Algorithms. Presented at 2023 IEEE 28th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Edinburgh, United Kingdom
Traditional permutation schemes mostly focus on random scrambling of pixels, often neglecting the intrinsic image information that could enhance diffusion in image encryption ...

A Self-Attention-Based Deep Convolutional Neural Networks for IIoT Networks Intrusion Detection

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, 12, 45762-45772. 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 susceptibi...

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