Tianhao Wang

According to our database, Tianhao Wang authored at least 59 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of two.

2024

Machine Unlearning of Pre-trained Large Language Models.

Jin Yao, Eli Chien, Minxin Du, Xinyao Niu, Tianhao Wang, Zezhou Cheng, Xiang Yue

CoRR, 2024

VGMShield: Mitigating Misuse of Video Generative Models.

Yan Pang, Yang Zhang, Tianhao Wang

CoRR, 2024

Backdoor Attacks via Machine Unlearning.

Zihao Liu, Tianhao Wang, Mengdi Huai, Chenglin Miao

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Differentially Private Vertical Federated Clustering.

Zitao Li, Tianhao Wang, Ninghui Li

Proc. VLDB Endow., 2023

Practical Differentially Private and Byzantine-resilient Federated Learning.

Zihang Xiang, Tianhao Wang, Wanyu Lin, Di Wang

Proc. ACM Manag. Data, 2023

PURE: A Framework for Analyzing Proximity-based Contact Tracing Protocols.

Fabrizio Cicala, Weicheng Wang, Tianhao Wang, Ninghui Li, Elisa Bertino, Faming Liang, Yang Yang

ACM Comput. Surv., 2023

Black-box Membership Inference Attacks against Fine-tuned Diffusion Models.

Yan Pang, Tianhao Wang

CoRR, 2023

A Somewhat Robust Image Watermark against Diffusion-based Editing Models.

Mingtian Tan, Tianhao Wang, Somesh Jha

CoRR, 2023

Meticulously Selecting 1% of the Dataset for Pre-training! Generating Differentially Private Images Data with Semantics Query.

Kecen Li, Chen Gong, Zhixiang Li, Yuzhong Zhao, Xinwen Hou, Tianhao Wang

CoRR, 2023

Preserving Node-level Privacy in Graph Neural Networks.

Zihang Xiang, Tianhao Wang, Di Wang

CoRR, 2023

Last One Standing: A Comparative Analysis of Security and Privacy of Soft Prompt Tuning, LoRA, and In-Context Learning.

Rui Wen, Tianhao Wang, Michael Backes, Yang Zhang, Ahmed Salem

CoRR, 2023

White-box Membership Inference Attacks against Diffusion Models.

Yan Pang, Tianhao Wang, Xuhui Kang, Mengdi Huai, Yang Zhang

CoRR, 2023

Pareto-Secure Machine Learning (PSML): Fingerprinting and Securing Inference Serving Systems.

Debopam Sanyal, Jui-Tse Hung, Manav Agrawal, Prahlad Jasti, Shahab Nikkhoo, Somesh Jha, Tianhao Wang, Sibin Mohan, Alexey Tumanov

CoRR, 2023

Differentially Private Wireless Federated Learning Using Orthogonal Sequences.

Xizixiang Wei, Tianhao Wang, Ruiquan Huang, Cong Shen, Jing Yang, H. Vincent Poor

CoRR, 2023

GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces.

Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David Evans

CoRR, 2023

A Plot is Worth a Thousand Words: Model Information Stealing Attacks via Scientific Plots.

Boyang Zhang, Xinlei He, Yun Shen, Tianhao Wang, Yang Zhang

Proceedings of the 32nd USENIX Security Symposium, 2023

PrivTrace: Differentially Private Trajectory Synthesis by Adaptive Markov Models.

Haiming Wang, Zhikun Zhang, Tianhao Wang, Shibo He, Michael Backes, Jiming Chen, Yang Zhang

Proceedings of the 32nd USENIX Security Symposium, 2023

FACE-AUDITOR: Data Auditing in Facial Recognition Systems.

Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Yang Zhang

Proceedings of the 32nd USENIX Security Symposium, 2023

GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces.

Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David E. Evans

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Is Adversarial Training Really a Silver Bullet for Mitigating Data Poisoning?

Rui Wen, Zhengyu Zhao, Zhuoran Liu, Michael Backes, Tianhao Wang, Yang Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

FLORAS: Differentially Private Wireless Federated Learning Using Orthogonal Sequences.

Xizixiang Wei, Tianhao Wang, Ruiquan Huang, Cong Shen, Jing Yang, H. Vincent Poor

Proceedings of the IEEE International Conference on Communications, 2023

Securely Sampling Discrete Gaussian Noise for Multi-Party Differential Privacy.

Chengkun Wei, Ruijing Yu, Yuan Fan, Wenzhi Chen, Tianhao Wang

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass.

Minxin Du, Xiang Yue, Sherman S. M. Chow, Tianhao Wang, Chenyu Huang, Huan Sun

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

Mitigating Membership Inference Attacks via Weighted Smoothing.

Mingtian Tan, Xiaofei Xie, Jun Sun, Tianhao Wang

Proceedings of the Annual Computer Security Applications Conference, 2023

Differentially Private Resource Allocation.

Joann Qiongna Chen, Tianhao Wang, Zhikun Zhang, Yang Zhang, Somesh Jha, Zhou Li

Proceedings of the Annual Computer Security Applications Conference, 2023

2022

PrivTrace: Differentially Private Trajectory Synthesis by Adaptive Markov Model.

Haiming Wang, Zhikun Zhang, Tianhao Wang, Shibo He, Michael Backes, Jiming Chen, Yang Zhang

CoRR, 2022

Memorization in NLP Fine-tuning Methods.

Fatemehsadat Mireshghallah, Archit Uniyal, Tianhao Wang, David Evans, Taylor Berg-Kirkpatrick

CoRR, 2022

Using Illustrations to Communicate Differential Privacy Trust Models: An Investigation of Users' Comprehension, Perception, and Data Sharing Decision.

Aiping Xiong, Chuhao Wu, Tianhao Wang, Robert W. Proctor, Jeremiah Blocki, Ninghui Li, Somesh Jha

CoRR, 2022

Locally Differentially Private Sparse Vector Aggregation.

Mingxun Zhou, Tianhao Wang, T.-H. Hubert Chan, Giulia Fanti, Elaine Shi

Proceedings of the 43rd IEEE Symposium on Security and Privacy, 2022

PFed-LDP: A Personalized Federated Local Differential Privacy Framework for IoT Sensing Data.

Jiechao Gao, Mingyue Tang, Tianhao Wang, Bradford Campbell

Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems, 2022

An Empirical Analysis of Memorization in Fine-tuned Autoregressive Language Models.

Fatemehsadat Mireshghallah, Archit Uniyal, Tianhao Wang, David E. Evans, Taylor Berg-Kirkpatrick

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Federated Boosted Decision Trees with Differential Privacy.

Samuel Maddock, Graham Cormode, Tianhao Wang, Carsten Maple, Somesh Jha

Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

Graph Unlearning.

Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang

Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

2021

Locally Differentially Private Heavy Hitter Identification.

Tianhao Wang, Ninghui Li, Somesh Jha

IEEE Trans. Dependable Secur. Comput., 2021

DPSyn: Experiences in the NIST Differential Privacy Data Synthesis Challenges.

Tianhao Wang, Ninghui Li, Zhikun Zhang

J. Priv. Confidentiality, 2021

PrivSyn: Differentially Private Data Synthesis.

Zhikun Zhang, Tianhao Wang, Ninghui Li, Jean Honorio, Michael Backes, Shibo He, Jiming Chen, Yang Zhang

Proceedings of the 30th USENIX Security Symposium, 2021

MGD: A Utility Metric for Private Data Publication.

Zitao Li, Trung Dang, Tianhao Wang, Ninghui Li

Proceedings of the 8th NSysS 2021: 8th International Conference on Networking, Systems and Security, Cox's Bazar, Bangladesh, December 21, 2021

When Machine Unlearning Jeopardizes Privacy.

Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang

Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

Continuous Release of Data Streams under both Centralized and Local Differential Privacy.

Tianhao Wang, Joann Qiongna Chen, Zhikun Zhang, Dong Su, Yueqiang Cheng, Zhou Li, Ninghui Li, Somesh Jha

Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

Differential Privacy for Text Analytics via Natural Text Sanitization.

Xiang Yue, Minxin Du, Tianhao Wang, Yaliang Li, Huan Sun, Sherman S. M. Chow

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020

Answering Multi-Dimensional Range Queries under Local Differential Privacy.

Jianyu Yang, Tianhao Wang, Ninghui Li, Xiang Cheng, Sen Su

Proc. VLDB Endow., 2020

Collecting and Analyzing Data Jointly from Multiple Services under Local Differential Privacy.

Min Xu, Bolin Ding, Tianhao Wang, Jingren Zhou

Proc. VLDB Endow., 2020

Improving Utility and Security of the Shuffler-based Differential Privacy.

Tianhao Wang, Min Xu, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang, Ninghui Li, Somesh Jha

Proc. VLDB Endow., 2020

Towards Effective Differential Privacy Communication for Users' Data Sharing Decision and Comprehension.

Aiping Xiong, Tianhao Wang, Ninghui Li, Somesh Jha

Proceedings of the 2020 IEEE Symposium on Security and Privacy, 2020

Estimating Numerical Distributions under Local Differential Privacy.

Zitao Li, Tianhao Wang, Milan Lopuhaä-Zwakenberg, Ninghui Li, Boris Skoric

Proceedings of the 2020 International Conference on Management of Data, 2020

Locally Differentially Private Frequency Estimation with Consistency.

Tianhao Wang, Milan Lopuhaä-Zwakenberg, Zitao Li, Boris Skoric, Ninghui Li

Proceedings of the 27th Annual Network and Distributed System Security Symposium, 2020

2019

DPSAaS: Multi-Dimensional Data Sharing and Analytics as Services under Local Differential Privacy.

Min Xu, Tianhao Wang, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang

Proc. VLDB Endow., 2019

Practical and Robust Privacy Amplification with Multi-Party Differential Privacy.

Tianhao Wang, Min Xu, Bolin Ding, Jingren Zhou, Ninghui Li, Somesh Jha

CoRR, 2019

Consistent and Accurate Frequency Oracles under Local Differential Privacy.

Tianhao Wang, Zitao Li, Ninghui Li, Milan Lopuhaä-Zwakenberg, Boris Skoric

CoRR, 2019

Answering Multi-Dimensional Analytical Queries under Local Differential Privacy.

Tianhao Wang, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang, Ninghui Li, Somesh Jha

Proceedings of the 2019 International Conference on Management of Data, 2019

Koinonia: verifiable e-voting with long-term privacy.

Huangyi Ge, Sze Yiu Chau, Victor E. Gonsalves, Huian Li, Tianhao Wang, Xukai Zou, Ninghui Li

Proceedings of the 35th Annual Computer Security Applications Conference, 2019

2018

Locally Differentially Private Frequent Itemset Mining.

Tianhao Wang, Ninghui Li, Somesh Jha

Proceedings of the 2018 IEEE Symposium on Security and Privacy, 2018

Privacy at Scale: Local Differential Privacy in Practice.

Graham Cormode, Somesh Jha, Tejas Kulkarni, Ninghui Li, Divesh Srivastava, Tianhao Wang

Proceedings of the 2018 International Conference on Management of Data, 2018

CALM: Consistent Adaptive Local Marginal for Marginal Release under Local Differential Privacy.

Zhikun Zhang, Tianhao Wang, Ninghui Li, Shibo He, Jiming Chen

Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, 2018

2017

Optimizing Locally Differentially Private Protocols.

Tianhao Wang, Jeremiah Blocki, Ninghui Li, Somesh Jha

CoRR, 2017

Locally Differentially Private Protocols for Frequency Estimation.

Tianhao Wang, Jeremiah Blocki, Ninghui Li, Somesh Jha

Proceedings of the 26th USENIX Security Symposium, 2017

2016

Secure Dynamic SSE via Access Indistinguishable Storage.

Tianhao Wang, Yunlei Zhao

Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security, 2016

On the Security and Usability of Segment-based Visual Cryptographic Authentication Protocols.

Tianhao Wang, Huangyi Ge, Omar Chowdhury, Hemanta K. Maji, Ninghui Li

Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, 2016

2014

Weight Balancing on Boundaries and Skeletons.

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

Proceedings of the 30th Annual Symposium on Computational Geometry, 2014