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)
SoK: Data Reconstruction Attacks Against Machine Learning Models: Definition, Metrics, and Benchmark
IEEE Symposium on Security and Privacy (S&P)
GPTracker: A Large-Scale Measurement of Misused GPTs
IEEE Symposium on Security and Privacy (S&P)
On the Effectiveness of Prompt Stealing Attacks on In-The-Wild Prompts
Usenix Security Symposium (USENIX-Security)
Usenix Security Symposium (USENIX-Security)
HateBench: Benchmarking Hate Speech Detectors on LLM-Generated Content and Hate Campaigns
International Conference on Learning Representations (ICLR)
SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation
Network and Distributed System Security Symposium (NDSS)
Understanding Data Importance in Machine Learning Attacks: Does Valuable Data Pose Greater Harm?
Security and Safety Preface: Security and safety of data in cloud computing
Security and Safety Advancing membership inference attacks: The present and the future
Annual Meeting of the Association for Computational Linguistics (ACL)
Are We in the AI-Generated Text World Already? Quantifying and Monitoring AIGT on Social Media