Outputs (4)

Leveraging LLMs for Non-Security Experts in Threat Hunting: Detecting Living off the Land Techniques (2025)
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 Living off the Land (LotL) techniques. LotL methods allow threat actors to blend... Read More about Leveraging LLMs for Non-Security Experts in Threat Hunting: Detecting Living off the Land Techniques.

VisCrypt: Image Encryption Featuring Novel Chaotic Key Generation and Block Permutation Techniques with Visual Cryptography (2024)
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. In this regards, this paper presents a robust image encryption scheme named... Read More about VisCrypt: Image Encryption Featuring Novel Chaotic Key Generation and Block Permutation Techniques with Visual Cryptography.

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.

PASSION: Permissioned Access Control for Segmented Devices and Identity for IoT Networks (2023)
Presentation / Conference Contribution
Ali, H., Abubakar, M., Ahmad, J., Buchanan, W. J., & Jaroucheh, Z. (2023, November). PASSION: Permissioned Access Control for Segmented Devices and Identity for IoT Networks. Presented at 2023 IEEE 28th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Edinburgh, United Kingdom

In recent years, there has been a significant proliferation of industrial Internet of Things (IoT) applications, with a wide variety of use cases being developed and put into operation. As the industrial IoT landscape expands, the establishment of se... Read More about PASSION: Permissioned Access Control for Segmented Devices and Identity for IoT Networks.