15 citations · 19 across the 13 of their papers we have counts for
4 papers · 1 filter
STAC: When Innocent Tools Form Dangerous Chains for LLM Agents
Jing-Jing Li, Jianfeng He, Chao Shang +6
As LLMs advance into autonomous agents with tool-use capabilities, they introduce security challenges that extend beyond traditional content-based LLM safety concerns. This paper i…
On the Vulnerability of Applying Retrieval-Augmented Generation within Knowledge-Intensive Application Domains
Xun Xian, Ganghua Wang, Xuan Bi +5
Retrieval-Augmented Generation (RAG) has been empirically shown to enhance the performance of large language models (LLMs) in knowledge-intensive domains such as healthcare, financ…
Demystifying Poisoning Backdoor Attacks from a Statistical Perspective
Ganghua Wang, Xun Xian, Jayanth Srinivasa +4
The growing dependence on machine learning in real-world applications emphasizes the importance of understanding and ensuring its safety. Backdoor attacks pose a significant securi…
Imitation Privacy
Xun Xian, Xinran Wang, Mingyi Hong +2
In recent years, there have been many cloud-based machine learning services, where well-trained models are provided to users on a pay-per-query scheme through a prediction API. The…