activity
20212026
most citedSeeing is Living? Rethinking the Security of Facial Liveness Verification in the Deepfake Era

13 citations · 53 across the 29 of their papers we have counts for

collaborators
Showing 2024Show all

6 papers · 1 filter

cs.CR2024

CopyrightMeter: Revisiting Copyright Protection in Text-to-image Models

Naen Xu, Changjiang Li, Tianyu Du +8

Text-to-image diffusion models have emerged as powerful tools for generating high-quality images from textual descriptions. However, their increasing popularity has raised signific…

cs.CR2024★ 1 cited

RobustKV: Defending Large Language Models against Jailbreak Attacks via KV Eviction

Tanqiu Jiang, Zian Wang, Jiacheng Liang +3

Jailbreak attacks circumvent LLMs' built-in safeguards by concealing harmful queries within jailbreak prompts. While existing defenses primarily focus on mitigating the effects of…

cs.CR2024★ 1 cited

Watch the Watcher! Backdoor Attacks on Security-Enhancing Diffusion Models

Changjiang Li, Ren Pang, Bochuan Cao +4

Thanks to their remarkable denoising capabilities, diffusion models are increasingly being employed as defensive tools to reinforce the security of other models, notably in purifyi…

cs.CR2024

Rethinking the Vulnerabilities of Face Recognition Systems:From a Practical Perspective

Jiahao Chen, Zhiqiang Shen, Yuwen Pu +5

Face Recognition Systems (FRS) have increasingly integrated into critical applications, including surveillance and user authentication, highlighting their pivotal role in modern se…

cs.SE2024

When Large Language Models Confront Repository-Level Automatic Program Repair: How Well They Done?

Yuxiao Chen, Jingzheng Wu, Xiang Ling +4

In recent years, large language models (LLMs) have demonstrated substantial potential in addressing automatic program repair (APR) tasks. However, the current evaluation of these m…

cs.CR2024

PRSA: Prompt Stealing Attacks against Real-World Prompt Services

Yong Yang, Changjiang Li, Qingming Li +6

Recently, large language models (LLMs) have garnered widespread attention for their exceptional capabilities. Prompts are central to the functionality and performance of LLMs, maki…