127 citations · 434 across the 18 of their papers we have counts for
18 papers
Navigating Pitfalls: Evaluating LLMs in Machine Learning Programming Education
Smitha Kumar, Michael A. Lones, Manuel Maarek +1
The rapid advancement of Large Language Models (LLMs) has opened new avenues in education. This study examines the use of LLMs in supporting learning in machine learning education;…
Self-Supervised Learning for Pre-training Capsule Networks: Overcoming Medical Imaging Dataset Challenges
Heba El-Shimy, Hind Zantout, Michael A. Lones +1
Deep learning techniques are increasingly being adopted in diagnostic medical imaging. However, the limited availability of high-quality, large-scale medical datasets presents a si…
GeMID: Generalizable Models for IoT Device Identification
Kahraman Kostas, Rabia Yasa Kostas, Mike Just +1
With the proliferation of devices on the Internet of Things (IoT), ensuring their security has become paramount. Device identification (DI), which distinguishes IoT devices based o…
Individual Packet Features are a Risk to Model Generalisation in ML-Based Intrusion Detection
Kahraman Kostas, Mike Just, Michael A. Lones
Machine learning is increasingly used for intrusion detection in IoT networks. This paper explores the effectiveness of using individual packet features (IPF), which are attributes…
ActDroid: An active learning framework for Android malware detection
Ali Muzaffar, Hani Ragab Hassen, Hind Zantout +1
The growing popularity of Android requires malware detection systems that can keep up with the pace of new software being released. According to a recent study, a new piece of malw…
IoTGeM: Generalizable Models for Behaviour-Based IoT Attack Detection
Kahraman Kostas, Mike Just, Michael A. Lones
Previous research on behavior-based attack detection for networks of IoT devices has resulted in machine learning models whose ability to adapt to unseen data is limited and often…