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...

Addressing Noise and Stochasticity in Fraud Detection for Service Networks

Fraud detection is crucial in social service networks to maintain user trust and improve service network security. Existing spectral graph-based methods address this challenge by leveraging different graph filters to capture signals with different frequencies in service networks. However, most...