4 papers
Breaking the Secret: Economic Interventions for Combating Collusion in Embodied Multi-Agent Systems
Qi Liu, Xiaohui Chen, Zhihui Zhao +5
Collusion among autonomous agents poses a critical security threat in embodied multi-agent systems (MAS), where coordinated behaviors can deviate from global objectives and lead to…
Lightweight Yet Secure: Secure Scripting Language Generation via Lightweight LLMs
Keyang Zhang, Zeyu Chen, Xuan Feng +4
The security of scripting languages such as PowerShell is critical given their powerful automation and administration capabilities, often exercised with elevated privileges. Today,…
Harnessing the Power of LLM to Support Binary Taint Analysis
Puzhuo Liu, Chengnian Sun, Yaowen Zheng +8
This paper proposes LATTE, the first static binary taint analysis that is powered by a large language model (LLM). LATTE is superior to the state of the art (e.g., Emtaint, Arbiter…
How Effective Are They? Exploring Large Language Model Based Fuzz Driver Generation
Cen Zhang, Yaowen Zheng, Mingqiang Bai +6
LLM-based (Large Language Model) fuzz driver generation is a promising research area. Unlike traditional program analysis-based method, this text-based approach is more general and…