Residual Observability and Attack Detectability in Encrypted OPC UA Traffic

OPC Unified Architecture OPC UA encryption conceals application-layer semantics and restricts intrusion detection to residual communication structure. Although machine learning-based intrusion detection systems IDSs can detect attacks in encrypted OPC UA traffic, the relationship between residual...

Multi-Level Distributional Entropy for Explainable Network Intrusion Detection

Machine learning network intrusion detection systems IDS rely on aggregate flow statistics that discard distributional structure, while established entropy measures require raw packet sequences unavailable in pre-aggregated flow datasets. We propose Multi-Level Distributional Entropy MDE, an...

Byte-Level Generative Predictions for Forensics Multimedia Carving

Digital forensic investigations often face significant challenges when recovering fragmented multimedia files that lack file system metadata. While traditional file carving relies on signatures and discriminative deep learning models for fragment classification, these methods cannot reconstruct o...

A Novel Solution for Zero-Day Attack Detection in IDS Using Self-Attention and Jensen-Shannon Divergence in WGAN-GP

The increasing sophistication of cyber threats, especially zero-day attacks, poses a significant challenge to cybersecurity. Zero-day attacks exploit unknown vulnerabilities, making them difficult to detect and defend against. Existing approaches patch flaws and deploy an Intrusion Detection Syst...