A Systematic Literature Review for Transformer-Based Software Vulnerability Detection

Context: Software vulnerabilities pose significant security threats to software systems, especially as software is increasingly used across many areas of daily life, including health, government, and finance. Recently, transformer-based models have demonstrated promising results in automatic...

ExAI5G: A Logic-Based Explainable AI Framework for Intrusion Detection in 5G Networks

Intrusion detection systems IDSs for 5G networks must handle complex, high-volume traffic. Although opaque "black-box" models can achieve high accuracy, their lack of transparency hinders trust and effective operational response. We propose ExAI5G, a framework that prioritizes interpretability by...

Enhancing Security and Strengthening Defenses in Automated Short-Answer Grading Systems

This study examines vulnerabilities in transformer-based automated short-answer grading systems used in medical education, with a focus on how these systems can be manipulated through adversarial gaming strategies. Our research identifies three main types of gaming strategies that exploit the...

AiCEF - An AI-assisted cyber exercise content generation framework using named entity recognition

AiCEF is a tool implementing the accompanying framework 1 in order to harness the intelligence that is available from online resources, as well as threat groups' activities, arsenal eg. MITRE, to create relevant and timely cybersecurity exercise content. This way, we abstract the events from the...