3 papers
cs.CR2026
Open Models, Open Risks: Measuring Unsafe Generation in Text-to-Image Models In the Wild
Peilin Han, Yang Liu, Yilong Yang +4
Existing safety studies on text-to-image (T2I) jailbreaks are largely conducted in controlled in-the-lab settings, typically on a small number of canonical models. As a result, the…
cs.CR2025
ProvX: Generating Counterfactual-Driven Attack Explanations for Provenance-Based Detection
Weiheng Wu, Wei Qiao, Teng Li +4
Provenance graph-based intrusion detection systems are deployed on hosts to defend against increasingly severe Advanced Persistent Threat. Using Graph Neural Networks to detect the…
cs.CR2025
Slot: Provenance-Driven APT Detection through Graph Reinforcement Learning
Wei Qiao, Yebo Feng, Teng Li +4
Advanced Persistent Threats (APTs) represent sophisticated cyberattacks characterized by their ability to remain undetected within the victim system for extended periods, aiming to…