activity
20232026
most citedTPatch: A Triggered Physical Adversarial Patch

3 citations · 3 across the 4 of their papers we have counts for

collaborators

6 papers

cs.SD2026

Expose Your Disguise: Recovering Source Speaker Identity From Voice Conversion

Hanlei Zhang, Zhongming Ma, Mingyang Zhang +3

Voice conversion (VC) poses a significant threat to biometric security by allowing attackers to impersonate target speakers. In forensic contexts, recovering the source speaker's i…

cs.CR2026

PINA: Prompt Injection Attack against Navigation Agents

Jiani Liu, Yixin He, Lanlan Fan +5

Navigation agents powered by large language models (LLMs) convert natural language instructions into executable plans and actions. Compared to text-based applications, their securi…

cs.CR2025

Attention is All You Need to Defend Against Indirect Prompt Injection Attacks in LLMs

Yinan Zhong, Qianhao Miao, Yanjiao Chen +3

Large Language Models (LLMs) have been integrated into many applications (e.g., web agents) to perform more sophisticated tasks. However, LLM-empowered applications are vulnerable…

cs.RO2024

Exploring Adversarial Robustness of LiDAR-Camera Fusion Model in Autonomous Driving

Bo Yang, Xiaoyu Ji, Zizhi Jin +2

Our study assesses the adversarial robustness of LiDAR-camera fusion models in 3D object detection. We introduce an attack technique that, by simply adding a limited number of phys…

cs.CV2023

CamPro: Camera-based Anti-Facial Recognition

Wenjun Zhu, Yuan Sun, Jiani Liu +3

The proliferation of images captured from millions of cameras and the advancement of facial recognition (FR) technology have made the abuse of FR a severe privacy threat. Existing…

cs.CR20233 cited

TPatch: A Triggered Physical Adversarial Patch

Wenjun Zhu, Xiaoyu Ji, Yushi Cheng +2

Autonomous vehicles increasingly utilize the vision-based perception module to acquire information about driving environments and detect obstacles. Correct detection and classifica…