4 citations · 5 across the 7 of their papers we have counts for
7 papers
Distillability of LLM Security Logic: Predicting Attack Success Rate of Outline Filling Attack via Ranking Regression
Tianyu Zhang, Zihang Xi, Jingyu Hua +1
In the realm of black-box jailbreak attacks on large language models (LLMs), the feasibility of constructing a narrow safety proxy, a lightweight model designed to predict the atta…
CoDefend: Cross-Modal Collaborative Defense via Diffusion Purification and Prompt Optimization
Fengling Zhu, Boshi Liu, Jingyu Hua +1
Multimodal Large Language Models (MLLMs) have achieved remarkable success in tasks such as image captioning, visual question answering, and cross-modal reasoning by integrating vis…
RADS-Checker: Measuring Compliance with Right of Access by the Data Subject in Android Markets
Zhenhua Li, Zhanpeng Liang, Congcong Yao +2
The latest data protection regulations worldwide, such as the General Data Protection Regulation (GDPR), have established the Right of Access by the Data Subject (RADS), granting u…
The Fire Thief Is Also the Keeper: Balancing Usability and Privacy in Prompts
Zhili Shen, Zihang Xi, Ying He +3
The rapid adoption of online chatbots represents a significant advancement in artificial intelligence. However, this convenience brings considerable privacy concerns, as prompts ca…
Subtoxic Questions: Dive Into Attitude Change of LLM's Response in Jailbreak Attempts
Tianyu Zhang, Zixuan Zhao, Jiaqi Huang +2
As Large Language Models (LLMs) of Prompt Jailbreaking are getting more and more attention, it is of great significance to raise a generalized research paradigm to evaluate attack…
SGBA: A Stealthy Scapegoat Backdoor Attack against Deep Neural Networks
Ying He, Zhili Shen, Chang Xia +3
Outsourced deep neural networks have been demonstrated to suffer from patch-based trojan attacks, in which an adversary poisons the training sets to inject a backdoor in the obtain…
We Can Track You If You Take the Metro: Tracking Metro Riders Using Accelerometers on Smartphones
Jingyu Hua, Zhenyu Shen, Sheng Zhong
Motion sensors (e.g., accelerometers) on smartphones have been demonstrated to be a powerful side channel for attackers to spy on users' inputs on touchscreen. In this paper, we re…