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.
Proceedings on Privacy Enhancing TechnologiesLink Stealing Attacks Against Inductive Graph Neural Networks
Conference on Empirical Methods in Natural Language Processing (EMNLP)
Reconstruct Your Previous Conversations! Comprehensively Investigating Privacy Leakage Risks in Conversations with GPT Models
Usenix Security Symposium (USENIX-Security)
SecurityNet: Assessing Machine Learning Vulnerabilities on Public Models
ACM Conference on Computer and Communications Security (CCS)
"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models
Usenix Security Symposium (USENIX-Security)
Prompt Stealing Attacks Against Text-to-Image Generation Models
Usenix Security Symposium (USENIX-Security)
Instruction Backdoor Attacks Against Customized LLMs
Network and Distributed System Security Symposium (NDSS)
Towards Understanding Unsafe Video Generation
Advanced ScienceIntegrating Vision‐Language Models for Accelerated High‐Throughput Nutrition Screening
ACM ASIA Conference on Computer and Communications Security (AsiaCCS)
FAKEPCD: Fake Point Cloud Detection via Source Attribution
Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)
Composite Backdoor Attacks Against Large Language Models