Faculty
2022: Busy Beaver Award für "Privacy of Machine Learning"
2019: Best paper award at NDSS
Dr. Yang Zhang ist Faculty am CISPA. Seine Forschung konzentriert sich auf Trustworthy Machine Learning (Privacy, Safety und Security). Außerdem arbeitet er an der Messung und dem Verständnis von Fehlinformationen und unsicheren Inhalten wie hasserfüllten Memes im Internet. Im Laufe der Jahre hat er zahlreiche Paper auf Spitzenkonferenzen in Informatik, einschließlich CCS, NDSS, Oakland und USENIX Security veröffentlicht. Seine Arbeit hat 2019 den NDSS Distinguished Paper Award und 2022 den CCS Best Paper Award Runner-up erhalten.
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)
HateBench: Benchmarking Hate Speech Detectors on LLM-Generated Content and Hate Campaigns
Usenix Security Symposium (USENIX-Security)
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
Privacy Enhancing Technologies Symposium (PETS)
A Comprehensive Study of Privacy Risks in Curriculum Learning