Publications (9)
CBSeq: A Channel-level Behavior Sequence For Encrypted Malware Traffic Detection
Susu Cui, Cong Dong, Meng Shen +3
Machine learning and neural networks have become increasingly popular solutions for encrypted malware traffic detection. They mine and learn complex traffic patterns, enabling dete…
QLPro: Automated Code Vulnerability Discovery via LLM and Static Code Analysis Integration
Junze Hu, Xiangyu Jin, Yizhe Zeng +5
We introduce QLPro, a vulnerability detection framework that systematically integrates LLMs and static analysis tools to enable comprehensive vulnerability detection across entire…
Are Watermarks Bugs for Deepfake Detectors? Rethinking Proactive Forensics
Xiaoshuai Wu, Xin Liao, Bo Ou +2
AI-generated content has accelerated the topic of media synthesis, particularly Deepfake, which can manipulate our portraits for positive or malicious purposes. Before releasing th…
Enhancing Cloud Network Resilience via a Robust LLM-Empowered Multi-Agent Reinforcement Learning Framework
Yixiao Peng, Hao Hu, Feiyang Li +5
While virtualization and resource pooling empower cloud networks with structural flexibility and elastic scalability, they inevitably expand the attack surface and challenge cyber…
Winemaking: Extracting Essential Insights for Efficient Threat Detection in Audit Logs
Weiheng Wu, Wei Qiao, Wenhao Yan +5
Advanced Persistent Threats (APTs) are continuously evolving, leveraging their stealthiness and persistence to put increasing pressure on current provenance-based Intrusion Detecti…
E-DoH: Elegantly Detecting the Depths of Open DoH Service on the Internet
Cong Dong, Jiahai Yang, Yun Li +6
In recent years, DNS over Encrypted (DoE) methods have been regarded as a novel trend within the realm of the DNS ecosystem. In these DoE methods, DNS over HTTPS (DoH) provides enc…
Towards Secure Retrieval-Augmented Generation: A Comprehensive Review of Threats, Defenses and Benchmarks
Yanming Mu, Hao Hu, Feiyang Li +7
Retrieval-Augmented Generation (RAG) significantly mitigates the hallucinations and domain knowledge deficiency in large language models by incorporating external knowledge bases.…
MirageBackdoor: A Stealthy Attack that Induces Think-Well-Answer-Wrong Reasoning
Yizhe Zeng, Wei Zhang, Yunpeng Li +3
While Chain-of-Thought (CoT) prompting has become a standard paradigm for eliciting complex reasoning capabilities in Large Language Models, it inadvertently exposes a new attack s…
A Content-Preserving Secure Linguistic Steganography
Lingyun Xiang, Chengfu Ou, Xu He +2
Existing linguistic steganography methods primarily rely on content transformations to conceal secret messages. However, they often cause subtle yet looking-innocent deviations bet…