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.
Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)
Composite Backdoor Attacks Against Large Language Models
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