4 citations · 4 across the 4 of their papers we have counts for
7 papers
GroupGuard: A Framework for Modeling and Defending Collusive Attacks in Multi-Agent Systems
Yiling Tao, Xinran Zheng, Shuo Yang +2
While large language model-based agents demonstrate great potential in collaborative tasks, their interactivity also introduces security vulnerabilities. In this paper, we propose…
Large Language Models for Network Intrusion Detection Systems: Foundations, Implementations, and Future Directions
Shuo Yang, Xinran Zheng, Xinchen Zhang +5
Large Language Models (LLMs) have revolutionized various fields with their exceptional capabilities in understanding, processing, and generating human-like text. This paper investi…
Generative AI for Vulnerability Detection in 6G Wireless Networks: Advances, Case Study, and Future Directions
Shuo Yang, Xinran Zheng, Jinfeng Xu +4
The rapid advancement of 6G wireless networks, IoT, and edge computing has significantly expanded the cyberattack surface, necessitating more intelligent and adaptive vulnerability…
RealFactBench: A Benchmark for Evaluating Large Language Models in Real-World Fact-Checking
Shuo Yang, Yuqin Dai, Guoqing Wang +6
Large Language Models (LLMs) hold significant potential for advancing fact-checking by leveraging their capabilities in reasoning, evidence retrieval, and explanation generation. H…
Learning to Focus: Context Extraction for Efficient Code Vulnerability Detection with Language Models
Xinran Zheng, Xingzhi Qian, Huichi Zhou +4
Language models (LMs) show promise for vulnerability detection but struggle with long, real-world code due to sparse and uncertain vulnerability locations. These issues, exacerbate…
On Benchmarking Code LLMs for Android Malware Analysis
Yiling He, Hongyu She, Xingzhi Qian +4
Large Language Models (LLMs) have demonstrated strong capabilities in various code intelligence tasks. However, their effectiveness for Android malware analysis remains underexplor…