5 papers
Reassessing feature-based Android malware detection in a contemporary context
Ali Muzaffar, Hani Ragab Hassen, Hind Zantout +1
We report the findings of a reimplementation of 18 foundational studies in feature-based machine learning for Android malware detection, published during the period 2013-2023. Thes…
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…
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…
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…