4 papers
Contextual and Seasonal LSTMs for Time Series Anomaly Detection
Lingpei Zhang, Qingming Li, Yong Yang +4
Univariate time series (UTS), where each timestamp records a single variable, serve as crucial indicators in web systems and cloud servers. Anomaly detection in UTS plays an essent…
TrapSuffix: Proactive Defense Against Adversarial Suffixes in Jailbreaking
Mengyao Du, Han Fang, Haokai Ma +4
Suffix-based jailbreak attacks append an adversarial suffix, i.e., a short token sequence, to steer aligned LLMs into unsafe outputs. Since suffixes are free-form text, they admit…
StealthGraph: Exposing Domain-Specific Risks in LLMs through Knowledge-Graph-Guided Harmful Prompt Generation
Huawei Zheng, Xinqi Jiang, Sen Yang +3
Large language models (LLMs) are increasingly applied in specialized domains such as finance and healthcare, where they introduce unique safety risks. Domain-specific datasets of h…
APT-CGLP: Advanced Persistent Threat Hunting via Contrastive Graph-Language Pre-Training
Xuebo Qiu, Mingqi Lv, Yimei Zhang +4
Provenance-based threat hunting identifies Advanced Persistent Threats (APTs) on endpoints by correlating attack patterns described in Cyber Threat Intelligence (CTI) with provenan…