📝 Selected Publications

Tailor-made Face Privacy Protection via Class-wise Targeted Universal Adversarial Perturbations
[2025 TDSC], CCF A, IF: 7.5, JCR: Q1

Yushu Zhang, Zixuan Yang, Tao Wang*, Zhongyun Hua, and Jian Weng

• This paper proposes a user-specific universal mask for face privacy, which can map all face images of the same user to a pre-defined virtual identity.

Seeing is not Believing: An Identity Hider for Human Vision Privacy Protection
[2025 TBIOM] , IF: 5, JCR: Q2, [code]
Tao Wang, Yushu Zhang*, Zixuan Yang, Xiangli Xiao, Hua Zhang, Zhongyun Hua.

• This paper proposes an identity hider, which can prevents humans from observing the identity but allows machines to extract the identity.

Beyond Privacy: Generating Privacy-Preserving Faces Supporting Robust Image Authentication
[2025 TIFS], CCF A, IF: 8, JCR: Q1, [code] [TL;DR]
Tao Wang, Wenying Weng*, Xiangli Xiao, Zhongyun Hua, Yushu Zhang, Yuming Fang

• This paper proposes AIDPro, which can embed messages in a robust way for image authentication while altering identity for privacy protection.

Make Privacy Renewable! Generating Privacy-Preserving Faces Supporting Cancelable Biometric Recognition
[2024 ACM MM], CCF A, [code]
Tao Wang, Yushu Zhang*, Xiangli Xiao, Lin Yuan, Zhihua Xia, Jian Weng

• This paper proposes CanFG, which can embed virtual identity for supporting cancelable biometrics while removing physical identity for privacy protection.

Security and Privacy on Generative Data in AIGC: A Survey
[2024 CSUR], IF: 28, JCR: Q1, [reading list]
Tao Wang, Yushu Zhang*, Shuren Qi, Ruoyu Zhao, Zhihua Xia, and Jian Weng

• This survey reviews the security and privacy on generative data in AIGC, particularly for the first time analyzing them from the perspective of information security properties, including privacy, controllability, authenticity, and compliance.