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.
Usenix Security Symposium (USENIX-Security)
FACE-AUDITOR: Data Auditing in Facial Recognition Systems.
Usenix Security Symposium (USENIX-Security)
Usenix Security Symposium (USENIX-Security)
International Conference on Machine Learning (ICML)
Generated Graph Detection.
Annual Meeting of the Association for Computational Linguistics (ACL)
NOTABLE: Transferable Backdoor Attacks Against Prompt-based NLP Models
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image Encoders
IEEE Symposium on Security and Privacy (S&P)
Usenix Security Symposium (USENIX-Security)
Two-in-One: A Model Hijacking Attack Against Text Generation Models
IEEE Transactions on Dependable and Secure Computing VeriTrain: Validating MLaaS Training Efforts via Anomaly Detection
Usenix Security Symposium (USENIX-Security)
A Plot is Worth a Thousand Words: Model Information Stealing Attacks via Scientific Plots