Research Statement

Recent Publications

Unified privacy attacks

SecretGen: Privacy Recovery on Pre-trained Models via Distribution Discrimination

Zhuowen Yuan, Fan Wu, Yunhui Long, Chaowei Xiao, Bo Li.

ECCV 2022


LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis

Fan Wu, Yunhui Long, Ce Zhang, Bo Li.

IEEE Symposium on Security and Privacy (Oakland), 2022


Characterizing Attacks on Deep Reinforcement Learning

Xinlei Pan, Chaowei Xiao, Warren He, Jian Peng, Mingjie Sun, Jinfeng Yi, Bo Li, Dawn Song.

AAMAS 2022 (Oral Presentation)


Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks

Yuheng Zhang, Ruoxi Jia, Hengzhi Pei, Wenxiao Wang, Bo Li, Dawn Song.

CVPR 2020 (Oral Presentation)


How You Act Tells a Lot: Privacy-Leakage Attack on Deep Reinforcement Learning

​Xinlei Pan, Weiyao Wang, Xiaoshuai Zhang, Bo Li, Jinfeng Yi, Dawn Song.

International Conference on Autonomous Agents and Multiagent Systems (AAMAS). May, 2019


Privacy-preserving data generation

G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators

Yunhui Long*, Boxin Wang*, Zhuolin Yang, Bhavya Kailkhura, Aston Zhang, Carl A. Gunter, Bo Li.

NeurIPS 2021


DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation

Boxin Wang*, Fan Wu*, Yunhui Long*, Luka Rimanic, Ce Zhang, Bo Li.

CCS 2021


Application-Driven Privacy-Preserving Data Publishing with Correlated Attributes

Aria Rezaei, Chaowei Xiao, Jie Gao, Bo Li, Sirajum Munir.

Embedded Wireless Systems and Networks (EWSN 2021) (Best Paper Award)


Iterative classification for sanitizing large-scale datasets

​B. Li, Y. Vorobeychik, M. Li, and B. Malin.

ICDM 2015