Tianhao Wang

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 76

Top Topics

Diffusion Models

Differential Privacy

Top Venues

USENIX Security Symposium

Proc. VLDB Endow.

Publications

Chen Gong, Kecen Li, Jin Yao, Tianhao Wang
TrajDeleter: Enabling Trajectory Forgetting in Offline Reinforcement Learning Agents. CoRR (2024)
Jin Yao, Eli Chien, Minxin Du, Xinyao Niu, Tianhao Wang, Zezhou Cheng, Xiang Yue
Machine Unlearning of Pre-trained Large Language Models. ACL (1) (2024)
Kecen Li, Chen Gong, Zhixiang Li, Yuzhong Zhao, Xinwen Hou, Tianhao Wang
PrivImage: Differentially Private Synthetic Image Generation using Diffusion Models with Semantic-Aware Pretraining. USENIX Security Symposium (2024)
Jin Yao, Eli Chien, Minxin Du, Xinyao Niu, Tianhao Wang, Zezhou Cheng, Xiang Yue
Machine Unlearning of Pre-trained Large Language Models. CoRR (2024)
Yan Pang, Aiping Xiong, Yang Zhang, Tianhao Wang
Towards Understanding Unsafe Video Generation. CoRR (2024)
Zihao Liu, Tianhao Wang, Mengdi Huai, Chenglin Miao
Backdoor Attacks via Machine Unlearning. AAAI (2024)
Yan Pang, Yang Zhang, Tianhao Wang
VGMShield: Mitigating Misuse of Video Generative Models. CoRR (2024)
Mingtian Tan, Tianhao Wang, Somesh Jha
A Somewhat Robust Image Watermark against Diffusion-based Editing Models. CoRR (2023)
Rui Wen, Zhengyu Zhao, Zhuoran Liu, Michael Backes, Tianhao Wang, Yang Zhang
Is Adversarial Training Really a Silver Bullet for Mitigating Data Poisoning? ICLR (2023)
Joann Qiongna Chen, Tianhao Wang, Zhikun Zhang, Yang Zhang, Somesh Jha, Zhou Li
Differentially Private Resource Allocation. ACSAC (2023)
Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David Evans
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces. CoRR (2023)
Zihang Xiang, Tianhao Wang, Wanyu Lin, Di Wang
Practical Differentially Private and Byzantine-resilient Federated Learning. Proc. ACM Manag. Data 1 (2) (2023)
Fabrizio Cicala, Weicheng Wang, Tianhao Wang, Ninghui Li, Elisa Bertino, Faming Liang, Yang Yang
PURE: A Framework for Analyzing Proximity-based Contact Tracing Protocols. ACM Comput. Surv. 55 (2) (2023)
Minxin Du, Xiang Yue, Sherman S. M. Chow, Tianhao Wang, Chenyu Huang, Huan Sun
DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass. CoRR (2023)
Minxin Du, Xiang Yue, Sherman S. M. Chow, Tianhao Wang, Chenyu Huang, Huan Sun
DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass. CCS (2023)
Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David Evans
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces. NeurIPS (2023)
Yan Pang, Tianhao Wang, Xuhui Kang, Mengdi Huai, Yang Zhang
White-box Membership Inference Attacks against Diffusion Models. CoRR (2023)
Debopam Sanyal, Jui-Tse Hung, Manav Agrawal, Prahlad Jasti, Shahab Nikkhoo, Somesh Jha, Tianhao Wang, Sibin Mohan, Alexey Tumanov
Pareto-Secure Machine Learning (PSML): Fingerprinting and Securing Inference Serving Systems. CoRR (2023)
Haiming Wang, Zhikun Zhang, Tianhao Wang, Shibo He, Michael Backes, Jiming Chen, Yang Zhang
PrivTrace: Differentially Private Trajectory Synthesis by Adaptive Markov Models. USENIX Security Symposium (2023)
Boyang Zhang, Xinlei He, Yun Shen, Tianhao Wang, Yang Zhang
A Plot is Worth a Thousand Words: Model Information Stealing Attacks via Scientific Plots. USENIX Security Symposium (2023)
Mingtian Tan, Xiaofei Xie, Jun Sun, Tianhao Wang
Mitigating Membership Inference Attacks via Weighted Smoothing. ACSAC (2023)
Xizixiang Wei, Tianhao Wang, Ruiquan Huang, Cong Shen, Jing Yang, H. Vincent Poor
FLORAS: Differentially Private Wireless Federated Learning Using Orthogonal Sequences. ICC (2023)
Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Yang Zhang
FACE-AUDITOR: Data Auditing in Facial Recognition Systems. USENIX Security Symposium (2023)
Zihang Xiang, Tianhao Wang, Di Wang
Preserving Node-level Privacy in Graph Neural Networks. CoRR (2023)
Yan Pang, Tianhao Wang
Black-box Membership Inference Attacks against Fine-tuned Diffusion Models. CoRR (2023)
Rui Wen, Tianhao Wang, Michael Backes, Yang Zhang, Ahmed Salem
Last One Standing: A Comparative Analysis of Security and Privacy of Soft Prompt Tuning, LoRA, and In-Context Learning. CoRR (2023)
Zitao Li, Tianhao Wang, Ninghui Li
Differentially Private Vertical Federated Clustering. Proc. VLDB Endow. 16 (6) (2023)
Xizixiang Wei, Tianhao Wang, Ruiquan Huang, Cong Shen, Jing Yang, H. Vincent Poor
Differentially Private Wireless Federated Learning Using Orthogonal Sequences. CoRR (2023)
Mingxun Zhou, Tianhao Wang, T.-H. Hubert Chan, Giulia Fanti, Elaine Shi
Locally Differentially Private Sparse Vector Aggregation. IEEE Symposium on Security and Privacy (2022)
Samuel Maddock, Graham Cormode, Tianhao Wang, Carsten Maple, Somesh Jha
Federated Boosted Decision Trees with Differential Privacy. CCS (2022)
Fatemehsadat Mireshghallah, Archit Uniyal, Tianhao Wang, David Evans, Taylor Berg-Kirkpatrick
Memorization in NLP Fine-tuning Methods. CoRR (2022)
Jiechao Gao, Mingyue Tang, Tianhao Wang, Bradford Campbell
PFed-LDP: A Personalized Federated Local Differential Privacy Framework for IoT Sensing Data. SenSys (2022)
Aiping Xiong, Chuhao Wu, Tianhao Wang, Robert W. Proctor, Jeremiah Blocki, Ninghui Li, Somesh Jha
Using Illustrations to Communicate Differential Privacy Trust Models: An Investigation of Users' Comprehension, Perception, and Data Sharing Decision. CoRR (2022)
Haiming Wang, Zhikun Zhang, Tianhao Wang, Shibo He, Michael Backes, Jiming Chen, Yang Zhang
PrivTrace: Differentially Private Trajectory Synthesis by Adaptive Markov Model. CoRR (2022)
Fatemehsadat Mireshghallah, Archit Uniyal, Tianhao Wang, David Evans, Taylor Berg-Kirkpatrick
An Empirical Analysis of Memorization in Fine-tuned Autoregressive Language Models. EMNLP (2022)
Samuel Maddock, Graham Cormode, Tianhao Wang, Carsten Maple, Somesh Jha
Federated Boosted Decision Trees with Differential Privacy. CoRR (2022)
Zitao Li, Tianhao Wang, Ninghui Li
Differentially Private Vertical Federated Clustering. CoRR (2022)
Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang
Graph Unlearning. CCS (2022)
Ninghui Li, Zhikun Zhang, Tianhao Wang
DPSyn: Experiences in the NIST Differential Privacy Data Synthesis Challenges. CoRR (2021)
Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang
Graph Unlearning. CoRR (2021)
Xiang Yue, Minxin Du, Tianhao Wang, Yaliang Li, Huan Sun, Sherman S. M. Chow
Differential Privacy for Text Analytics via Natural Text Sanitization. CoRR (2021)
Tianhao Wang, Ninghui Li, Zhikun Zhang
DPSyn: Experiences in the NIST Differential Privacy Data Synthesis Challenges. J. Priv. Confidentiality 11 (2) (2021)
Tianhao Wang, Joann Qiongna Chen, Zhikun Zhang, Dong Su, Yueqiang Cheng, Zhou Li, Ninghui Li, Somesh Jha
Continuous Release of Data Streams under both Centralized and Local Differential Privacy. CCS (2021)
Zitao Li, Trung Dang, Tianhao Wang, Ninghui Li
MGD: A Utility Metric for Private Data Publication. NSysS (2021)
Zhikun Zhang, Tianhao Wang, Ninghui Li, Jean Honorio, Michael Backes, Shibo He, Jiming Chen, Yang Zhang
PrivSyn: Differentially Private Data Synthesis. USENIX Security Symposium (2021)
Mingxun Zhou, Tianhao Wang, T.-H. Hubert Chan, Giulia Fanti, Elaine Shi
Locally Differentially Private Sparse Vector Aggregation. CoRR (2021)
Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang
When Machine Unlearning Jeopardizes Privacy. CCS (2021)
Tianhao Wang, Ninghui Li, Somesh Jha
Locally Differentially Private Heavy Hitter Identification. IEEE Trans. Dependable Secur. Comput. 18 (2) (2021)
Xiang Yue, Minxin Du, Tianhao Wang, Yaliang Li, Huan Sun, Sherman S. M. Chow
Differential Privacy for Text Analytics via Natural Text Sanitization. ACL/IJCNLP (Findings) (2021)
Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang
When Machine Unlearning Jeopardizes Privacy. CoRR (2020)
Tianhao Wang, Min Xu, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang, Ninghui Li, Somesh Jha
Improving Utility and Security of the Shuffler-based Differential Privacy. Proc. VLDB Endow. 13 (13) (2020)
Jianyu Yang, Tianhao Wang, Ninghui Li, Xiang Cheng, Sen Su
Answering Multi-Dimensional Range Queries under Local Differential Privacy. Proc. VLDB Endow. 14 (3) (2020)
Min Xu, Bolin Ding, Tianhao Wang, Jingren Zhou
Collecting and Analyzing Data Jointly from Multiple Services under Local Differential Privacy. Proc. VLDB Endow. 13 (11) (2020)
Fabrizio Cicala, Weicheng Wang, Tianhao Wang, Ninghui Li, Elisa Bertino, Faming Liang, Yang Yang
PURE: A Framework for Analyzing Proximity-based Contact Tracing Protocols. CoRR (2020)
Aiping Xiong, Tianhao Wang, Ninghui Li, Somesh Jha
Towards Effective Differential Privacy Communication for Users' Data Sharing Decision and Comprehension. IEEE Symposium on Security and Privacy (2020)
Tianhao Wang, Joann Qiongna Chen, Zhikun Zhang, Dong Su, Yueqiang Cheng, Zhou Li, Ninghui Li, Somesh Jha
Continuous Release of Data Streams under both Centralized and Local Differential Privacy. CoRR (2020)
Jianyu Yang, Tianhao Wang, Ninghui Li, Xiang Cheng, Sen Su
Answering Multi-Dimensional Range Queries under Local Differential Privacy. CoRR (2020)
Zhikun Zhang, Tianhao Wang, Ninghui Li, Jean Honorio, Michael Backes, Shibo He, Jiming Chen, Yang Zhang
PrivSyn: Differentially Private Data Synthesis. CoRR (2020)
Tianhao Wang, Milan Lopuhaä-Zwakenberg, Zitao Li, Boris Skoric, Ninghui Li
Locally Differentially Private Frequency Estimation with Consistency. NDSS (2020)
Aiping Xiong, Tianhao Wang, Ninghui Li, Somesh Jha
Towards Effective Differential Privacy Communication for Users' Data Sharing Decision and Comprehension. CoRR (2020)
Zitao Li, Tianhao Wang, Milan Lopuhaä-Zwakenberg, Ninghui Li, Boris Skoric
Estimating Numerical Distributions under Local Differential Privacy. SIGMOD Conference (2020)
Tianhao Wang, Min Xu, Bolin Ding, Jingren Zhou, Ninghui Li, Somesh Jha
Practical and Robust Privacy Amplification with Multi-Party Differential Privacy. CoRR (2019)
Zitao Li, Tianhao Wang, Milan Lopuhaä-Zwakenberg, Boris Skoric, Ninghui Li
Estimating Numerical Distributions under Local Differential Privacy. CoRR (2019)
Tianhao Wang, Zitao Li, Ninghui Li, Milan Lopuhaä-Zwakenberg, Boris Skoric
Consistent and Accurate Frequency Oracles under Local Differential Privacy. CoRR (2019)
Tianhao Wang, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang, Ninghui Li, Somesh Jha
Answering Multi-Dimensional Analytical Queries under Local Differential Privacy. SIGMOD Conference (2019)
Min Xu, Tianhao Wang, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang
DPSAaS: Multi-Dimensional Data Sharing and Analytics as Services under Local Differential Privacy. Proc. VLDB Endow. 12 (12) (2019)
Huangyi Ge, Sze Yiu Chau, Victor E. Gonsalves, Huian Li, Tianhao Wang, Xukai Zou, Ninghui Li
Koinonia: verifiable e-voting with long-term privacy. ACSAC (2019)
Graham Cormode, Somesh Jha, Tejas Kulkarni, Ninghui Li, Divesh Srivastava, Tianhao Wang
Privacy at Scale: Local Differential Privacy in Practice. SIGMOD Conference (2018)
Tianhao Wang, Ninghui Li, Somesh Jha
Locally Differentially Private Frequent Itemset Mining. IEEE Symposium on Security and Privacy (2018)
Zhikun Zhang, Tianhao Wang, Ninghui Li, Shibo He, Jiming Chen
CALM: Consistent Adaptive Local Marginal for Marginal Release under Local Differential Privacy. CCS (2018)
Tianhao Wang, Jeremiah Blocki, Ninghui Li, Somesh Jha
Locally Differentially Private Protocols for Frequency Estimation. USENIX Security Symposium (2017)
Tianhao Wang, Jeremiah Blocki, Ninghui Li, Somesh Jha
Optimizing Locally Differentially Private Protocols. CoRR (2017)
Tianhao Wang, Ninghui Li, Somesh Jha
Locally Differentially Private Heavy Hitter Identification. CoRR (2017)
Tianhao Wang, Yunlei Zhao
Secure Dynamic SSE via Access Indistinguishable Storage. AsiaCCS (2016)
Tianhao Wang, Huangyi Ge, Omar Chowdhury, Hemanta K. Maji, Ninghui Li
On the Security and Usability of Segment-based Visual Cryptographic Authentication Protocols. CCS (2016)
Luis Barba, Otfried Cheong, Jean-Lou De Carufel, Michael Gene Dobbins, Rudolf Fleischer, Akitoshi Kawamura, Matias Korman, Yoshio Okamoto, János Pach, Yuan Tang, Takeshi Tokuyama, Sander Verdonschot, Tianhao Wang
Weight Balancing on Boundaries and Skeletons. CoRR (2015)
Luis Barba, Otfried Cheong, Jean-Lou De Carufel, Michael Gene Dobbins, Rudolf Fleischer, Akitoshi Kawamura, Matias Korman, Yoshio Okamoto, János Pach, Yuan Tang, Takeshi Tokuyama, Sander Verdonschot, Tianhao Wang
Weight Balancing on Boundaries and Skeletons. SoCG (2014)