Yunhui Long

Publication Activity (10 Years)

Years Active: 2013-2023
Publications (10 Years): 21

Top Topics

Differentially Private

Learning Models

Privacy Preserving

Hypothesis Test

Top Venues

IEEE Symposium on Security and Privacy

Publications

Yuzheng Hu, Fan Wu, Qinbin Li, Yunhui Long, Gonzalo Munilla Garrido, Chang Ge, Bolin Ding, David A. Forsyth, Bo Li, Dawn Song
SoK: Privacy-Preserving Data Synthesis. CoRR (2023)
Chulin Xie, Yunhui Long, Pin-Yu Chen, Qinbin Li, Sanmi Koyejo, Bo Li
Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks. CCS (2023)
Zhuowen Yuan, Fan Wu, Yunhui Long, Chaowei Xiao, Bo Li
SecretGen: Privacy Recovery on Pre-trained Models via Distribution Discrimination. ECCV (5) (2022)
Fan Wu, Yunhui Long, Ce Zhang, Bo Li
LINKTELLER: Recovering Private Edges from Graph Neural Networks via Influence Analysis. IEEE Symposium on Security and Privacy (2022)
Zhuowen Yuan, Fan Wu, Yunhui Long, Chaowei Xiao, Bo Li
SecretGen: Privacy Recovery on Pre-Trained Models via Distribution Discrimination. CoRR (2022)
Chulin Xie, Yunhui Long, Pin-Yu Chen, Bo Li
Uncovering the Connection Between Differential Privacy and Certified Robustness of Federated Learning against Poisoning Attacks. CoRR (2022)
Chulin Xie, Zhong Cao, Yunhui Long, Diange Yang, Ding Zhao, Bo Li
Privacy of Autonomous Vehicles: Risks, Protection Methods, and Future Directions. CoRR (2022)
Fan Wu, Yunhui Long, Ce Zhang, Bo Li
LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis. CoRR (2021)
Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation. CoRR (2021)
Boxin Wang, Fan Wu, Yunhui Long, Luka Rimanic, Ce Zhang, Bo Li
DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation. CCS (2021)
Yunhui Long, Boxin Wang, Zhuolin Yang, Bhavya Kailkhura, Aston Zhang, Carl A. Gunter, Bo Li
G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators. NeurIPS (2021)
Yunhui Long, Lei Wang, Diyue Bu, Vincent Bindschaedler, XiaoFeng Wang, Haixu Tang, Carl A. Gunter, Kai Chen
A Pragmatic Approach to Membership Inferences on Machine Learning Models. EuroS&P (2020)
Yunhui Long, Le Xu, Carl A. Gunter
A Hypothesis Testing Approach to Sharing Logs with Confidence. CODASPY (2020)
Vanishree Rao, Yunhui Long, Hoda Eldardiry, Shantanu Rane, Ryan A. Rossi, Frank Torres
Secure Two-Party Feature Selection. CoRR (2019)
Yunhui Long, Suxin Lin, Zhuolin Yang, Carl A. Gunter, Bo Li
Scalable Differentially Private Generative Student Model via PATE. CoRR (2019)
Avesta Hojjati, Yunhui Long, Soteris Demetriou, Carl A. Gunter
BEEER: distributed record and replay for medical devices in hospital operating rooms. HotSoS (2019)
Yunhui Long, Vincent Bindschaedler, Lei Wang, Diyue Bu, Xiaofeng Wang, Haixu Tang, Carl A. Gunter, Kai Chen
Understanding Membership Inferences on Well-Generalized Learning Models. CoRR (2018)
Xuejing Yuan, Yuxuan Chen, Yue Zhao, Yunhui Long, Xiaokang Liu, Kai Chen, Shengzhi Zhang, Heqing Huang, Xiaofeng Wang, Carl A. Gunter
CommanderSong: A Systematic Approach for Practical Adversarial Voice Recognition. CoRR (2018)
Yunhui Long, Tanmay Gangwani, Haris Mughees, Carl A. Gunter
Distributed and Secure ML with Self-tallying Multi-party Aggregation. CoRR (2018)
Xuejing Yuan, Yuxuan Chen, Yue Zhao, Yunhui Long, Xiaokang Liu, Kai Chen, Shengzhi Zhang, Heqing Huang, Xiaofeng Wang, Carl A. Gunter
CommanderSong: A Systematic Approach for Practical Adversarial Voice Recognition. USENIX Security Symposium (2018)
Yunhui Long, Vincent Bindschaedler, Carl A. Gunter
Towards Measuring Membership Privacy. CoRR (2017)
Mingyang Lv, Yunhui Long, Qianyun Zhang, Xinyu Sheng, Li Xu, Hang Guo, Wenbo Zhang, Xiaoguang Zhang
A fast polarimeter calibration method using vector projection algorithm. ICAIT (2013)