Practical Blind Membership Inference Attack via Differential Comparisons. - Bo Hui 002; Yuchen Yang 001; Haolin Yuan; Philippe Burlina; Neil Zhenqiang Gong; Yinzhi Cao (NDSS, 2021)

Addressing Heterogeneity in Federated Learning via Distributional Transformation. - Haolin Yuan; Bo Hui 002; Yuchen Yang 001; Philippe Burlina; Neil Zhenqiang Gong; Yinzhi Cao (ECCV (38), 2022)

Fortifying Federated Learning against Membership Inference Attacks via Client-level Input Perturbation. - Yuchen Yang 001; Haolin Yuan; Bo Hui 002; Neil Zhenqiang Gong; Neil Fendley; Philippe Burlina; Yinzhi Cao (DSN, 2023)

PrivateFL: Accurate, Differentially Private Federated Learning via Personalized Data Transformation. - Yuchen Yang 001; Bo Hui 002; Haolin Yuan; Neil Zhenqiang Gong; Yinzhi Cao (USENIX Security Symposium, 2023)

SneakyPrompt: Evaluating Robustness of Text-to-image Generative Models' Safety Filters. - Yuchen Yang 001; Bo Hui 002; Haolin Yuan; Neil Zhenqiang Gong; Yinzhi Cao (CoRR, 2023)

PLeak: Prompt Leaking Attacks against Large Language Model Applications. - Bo Hui 002; Haolin Yuan; Neil Gong 001; Philippe Burlina; Yinzhi Cao (CCS, 2024)

SneakyPrompt: Jailbreaking Text-to-image Generative Models. - Yuchen Yang 001; Bo Hui 002; Haolin Yuan; Neil Gong 001; Yinzhi Cao (SP, 2024)