Faculty
2022: Busy Beaver Award for "Privacy of Machine Learning"
2019: Best paper award at NDSS
Dr. YAng Zhang is Faculty at CISPA. His research concentrates on trustworthy machine learning (privacy, safety, and security). Moreover, he works on measuring and understanding misinformation and unsafe content like hateful memes on the Internet. Over the years, he has published multiple papers at top venues in computer science, including CCS, NDSS, Oakland, and USENIX Security. His work has received the NDSS 2019 distinguished paper award and the CCS 2022 best paper award runner-up.
IEEE Symposium on Security and Privacy Workshops (SPW)
You Only Prompt Once: On the Capabilities of Prompt Learning on Large Language Models to Tackle Toxic Content
International Conference on Web and Social Media (ICWSM)
Games and Beyond: Analyzing the Bullet Chats of Esports Livestreaming
International Conference on Acoustics Speech and Signal Processing (ICASSP)
Detection and Attribution of Models Trained on Generated Data
IEEE Workshop on Applications of Computer Vision (WACV)
Generated Distributions Are All You Need for Membership Inference Attacks Against Generative Models
Usenix Security Symposium (USENIX-Security)
Quantifying Privacy Risks of Prompts in Visual Prompt Learning
Annual Computer Security Applications Conference (ACSAC)
ACM Conference on Computer and Communications Security (CCS)
Unsafe Diffusion: On the Generation of Unsafe Images and
Hateful Memes From Text-To-Image Models
ACM Conference on Computer and Communications Security (CCS)
DE-FAKE: Detection and Attribution of Fake Images Generated by Text-to-Image Generation Models
IEEE Symposium on Security and Privacy (S&P)
Test-Time Poisoning Attacks Against Test-Time Adaptation Models
Usenix Security Symposium (USENIX-Security)
FACE-AUDITOR: Data Auditing in Facial Recognition Systems.