Formulating Subgroup Discovery As a Quantum Optimization Problem for Network Security

While current network intrusion detection systems achieve satisfactory accuracy, they often lack explainability. Subgroup Discovery SD addresses this by building interpretable rules that characterize feature interactions associated with attack traffic. With large datasets, classical heuristic bea...

A Non-Monotonic Relationship: an Empirical Analysis of Hybrid Quantum Classifiers for Unseen Ransomware Detection

Detecting unseen ransomware is a critical cybersecurity challenge where classical machine learning often fails. While Quantum Machine Learning QML presents a potential alternative, its application is hindered by the dimensionality gap between classical data and quantum hardware. This paper...