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Tianhao Wang 0001
Person information
- affiliation: University of Virginia, VA, USA
- affiliation (former): Carnegie Mellon University, Pittsburgh, PA, USA
- affiliation (former): Purdue University, West Lafayette, IN, USA
- affiliation (former): Fudan University, Shanghai, China
Other persons with the same name
- Tianhao Wang — disambiguation page
- Tianhao Wang 0002 — University of Science & Technology of China, Hefei, China
- Tianhao Wang 0003 — The University of Nottingham, Ningbo, China
- Tianhao Wang 0004 — Harbin Institute of Technology, Harbin, China
- Tianhao Wang 0005 — Rush University, Chicago, IL, USA (and 1 more)
- Tianhao Wang 0006 — University of Waterloo, ON, Canada
- Tianhao Wang 0007 — Harbin Engineering University, College of Underwater Acoustic Engineering, China
- Tianhao Wang 0008 — Communication University of China, School of Information Engineering, Beijing, China
- Tianhao Wang 0009 — Jilin University, College of Instrumentation and Electrical Engineering, Changchun, China
- Tianhao Wang 0010 — Fudan University, Zhongshan Hospital, Department of General Practice, Shanghai, China
- Tianhao Wang 0011 — Big Data Management Center, Yichang, China
- Tianhao Wang 0012 — Pacific Northwest National Laboratory, Richland, WA, USA (and 1 more)
- Tianhao Wang 0013 — Harvard University, Cambridge, MA, USA
- Tianhao Wang 0014 — Tsinghua University, Department of Engineering Physics / MoE Key Laboratory of Particle and Radiation Imaging, Beijing, China
- Tianhao Wang 0015 — China Three Gorges University, Big Data Research Center, Yichang, China
- Tianhao Wang 0016 — Southeast University, School of Computer Science and Engineering, Nanjing, China
- Tianhao Wang 0017 — Yale University, Department of Statistics and Data Science, New Haven, CT, USA
- Tianhao Wang 0018 — Fuzhou University, MoE Key Laboratory of Spatial Data Mining and Information Sharing, China
- Tianhao Wang 0019 — Sichuan University, College of Electronics and Information Engineering, Chengdu, China
- Tianhao Wang 0020 — State Grid Tianjin Electrical Power Company, Electric Power Research Institute, China
- Tianhao Wang 0021 — Princeton University, NJ, USA
- Tianhao Wang 0022 — Dalian University of Technology, School of Information and Communication Engineering, China
- Tianhao Wang 0023 — Spallation Neutron Source Science Center, Gongguan, China
- Tianhao Wang 0024 — Nanjing University, Department of Computer Science and Technology, State Key Laboratory for Novel Software Technology, China
- Tianhao Wang 0025 — ByteDance
- Tianhao Wang 0026 — University of Texas at Dallas, TX, USA
- Tianhao Wang 0027 — Northeast Forestry University, College of Computer and Control Engineering, Harbin, China (and 1 more)
- Tianhao Wang 0028 — Tongji University, School of Economics and Management, Shanghai, China
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2020 – today
- 2024
- [j10]Yuhan Liu, Tianhao Wang, Yixuan Liu, Hong Chen, Cuiping Li:
Edge-Protected Triangle Count Estimation Under Relationship Local Differential Privacy. IEEE Trans. Knowl. Data Eng. 36(10): 5138-5152 (2024) - [c37]Zihao Liu, Tianhao Wang, Mengdi Huai, Chenglin Miao:
Backdoor Attacks via Machine Unlearning. AAAI 2024: 14115-14123 - [c36]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: 8403-8419 - [c35]Chen Gong, Zhou Yang, Yunpeng Bai, Junda He, Jieke Shi, Kecen Li, Arunesh Sinha, Bowen Xu, Xinwen Hou, David Lo, Tianhao Wang:
Baffle: Hiding Backdoors in Offline Reinforcement Learning Datasets. SP 2024: 2086-2104 - [c34]Zihang Xiang, Tianhao Wang, Di Wang:
Preserving Node-level Privacy in Graph Neural Networks. SP 2024: 4714-4732 - [c33]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 - [i38]Yan Pang, Yang Zhang, Tianhao Wang:
VGMShield: Mitigating Misuse of Video Generative Models. CoRR abs/2402.13126 (2024) - [i37]Jin Yao, Eli Chien, Minxin Du, Xinyao Niu, Tianhao Wang, Zezhou Cheng, Xiang Yue:
Machine Unlearning of Pre-trained Large Language Models. CoRR abs/2402.15159 (2024) - [i36]Chen Gong, Kecen Li, Jin Yao, Tianhao Wang:
TrajDeleter: Enabling Trajectory Forgetting in Offline Reinforcement Learning Agents. CoRR abs/2404.12530 (2024) - [i35]Yan Pang, Aiping Xiong, Yang Zhang, Tianhao Wang:
Towards Understanding Unsafe Video Generation. CoRR abs/2407.12581 (2024) - 2023
- [j9]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): 3:1-3:36 (2023) - [j8]Zihang Xiang, Tianhao Wang, Wanyu Lin, Di Wang:
Practical Differentially Private and Byzantine-resilient Federated Learning. Proc. ACM Manag. Data 1(2): 119:1-119:26 (2023) - [j7]Zitao Li, Tianhao Wang, Ninghui Li:
Differentially Private Vertical Federated Clustering. Proc. VLDB Endow. 16(6): 1277-1290 (2023) - [c32]Joann Qiongna Chen, Tianhao Wang, Zhikun Zhang, Yang Zhang, Somesh Jha, Zhou Li:
Differentially Private Resource Allocation. ACSAC 2023: 772-786 - [c31]Mingtian Tan, Xiaofei Xie, Jun Sun, Tianhao Wang:
Mitigating Membership Inference Attacks via Weighted Smoothing. ACSAC 2023: 787-798 - [c30]Chengkun Wei, Ruijing Yu, Yuan Fan, Wenzhi Chen, Tianhao Wang:
Securely Sampling Discrete Gaussian Noise for Multi-Party Differential Privacy. CCS 2023: 2262-2276 - [c29]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: 2665-2679 - [c28]Xizixiang Wei, Tianhao Wang, Ruiquan Huang, Cong Shen, Jing Yang, H. Vincent Poor:
FLORAS: Differentially Private Wireless Federated Learning Using Orthogonal Sequences. ICC 2023: 3121-3126 - [c27]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 - [c26]Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David E. Evans:
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces. NeurIPS 2023 - [c25]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: 1649-1666 - [c24]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: 5289-5306 - [c23]Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Yang Zhang:
FACE-AUDITOR: Data Auditing in Facial Recognition Systems. USENIX Security Symposium 2023: 7195-7212 - [i34]Boyang Zhang, Xinlei He, Yun Shen, Tianhao Wang, Yang Zhang:
A Plot is Worth a Thousand Words: Model Information Stealing Attacks via Scientific Plots. CoRR abs/2302.11982 (2023) - [i33]Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David Evans:
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces. CoRR abs/2303.01621 (2023) - [i32]Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Yang Zhang:
FACE-AUDITOR: Data Auditing in Facial Recognition Systems. CoRR abs/2304.02782 (2023) - [i31]Zihang Xiang, Tianhao Wang, Wanyu Lin, Di Wang:
Practical Differentially Private and Byzantine-resilient Federated Learning. CoRR abs/2304.09762 (2023) - [i30]Xizixiang Wei, Tianhao Wang, Ruiquan Huang, Cong Shen, Jing Yang, H. Vincent Poor:
Differentially Private Wireless Federated Learning Using Orthogonal Sequences. CoRR abs/2306.08280 (2023) - [i29]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 abs/2307.01292 (2023) - [i28]Yan Pang, Tianhao Wang, Xuhui Kang, Mengdi Huai, Yang Zhang:
White-box Membership Inference Attacks against Diffusion Models. CoRR abs/2308.06405 (2023) - [i27]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 abs/2309.06746 (2023) - [i26]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 abs/2310.11397 (2023) - [i25]Zihang Xiang, Tianhao Wang, Di Wang:
Preserving Node-level Privacy in Graph Neural Networks. CoRR abs/2311.06888 (2023) - [i24]Kecen Li, Chen Gong, Zhixiang Li, Yuzhong Zhao, Xinwen Hou, Tianhao Wang:
Meticulously Selecting 1% of the Dataset for Pre-training! Generating Differentially Private Images Data with Semantics Query. CoRR abs/2311.12850 (2023) - [i23]Mingtian Tan, Tianhao Wang, Somesh Jha:
A Somewhat Robust Image Watermark against Diffusion-based Editing Models. CoRR abs/2311.13713 (2023) - [i22]Yan Pang, Tianhao Wang:
Black-box Membership Inference Attacks against Fine-tuned Diffusion Models. CoRR abs/2312.08207 (2023) - 2022
- [c22]Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang:
Graph Unlearning. CCS 2022: 499-513 - [c21]Samuel Maddock, Graham Cormode, Tianhao Wang, Carsten Maple, Somesh Jha:
Federated Boosted Decision Trees with Differential Privacy. CCS 2022: 2249-2263 - [c20]Fatemehsadat Mireshghallah, Archit Uniyal, Tianhao Wang, David E. Evans, Taylor Berg-Kirkpatrick:
An Empirical Analysis of Memorization in Fine-tuned Autoregressive Language Models. EMNLP 2022: 1816-1826 - [c19]Jiechao Gao, Mingyue Tang, Tianhao Wang, Bradford Campbell:
PFed-LDP: A Personalized Federated Local Differential Privacy Framework for IoT Sensing Data. SenSys 2022: 835-836 - [c18]Mingxun Zhou, Tianhao Wang, T.-H. Hubert Chan, Giulia Fanti, Elaine Shi:
Locally Differentially Private Sparse Vector Aggregation. SP 2022: 422-439 - [i21]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 abs/2202.10014 (2022) - [i20]Fatemehsadat Mireshghallah, Archit Uniyal, Tianhao Wang, David Evans, Taylor Berg-Kirkpatrick:
Memorization in NLP Fine-tuning Methods. CoRR abs/2205.12506 (2022) - [i19]Zitao Li, Tianhao Wang, Ninghui Li:
Differentially Private Vertical Federated Clustering. CoRR abs/2208.01700 (2022) - [i18]Haiming Wang, Zhikun Zhang, Tianhao Wang, Shibo He, Michael Backes, Jiming Chen, Yang Zhang:
PrivTrace: Differentially Private Trajectory Synthesis by Adaptive Markov Model. CoRR abs/2210.00581 (2022) - [i17]Samuel Maddock, Graham Cormode, Tianhao Wang, Carsten Maple, Somesh Jha:
Federated Boosted Decision Trees with Differential Privacy. CoRR abs/2210.02910 (2022) - 2021
- [b1]Tianhao Wang:
Analyzing Sensitive Data with Local Differential Privacy. Purdue University, USA, 2021 - [j6]Tianhao Wang, Ninghui Li, Zhikun Zhang:
DPSyn: Experiences in the NIST Differential Privacy Data Synthesis Challenges. J. Priv. Confidentiality 11(2) (2021) - [j5]Tianhao Wang, Ninghui Li, Somesh Jha:
Locally Differentially Private Heavy Hitter Identification. IEEE Trans. Dependable Secur. Comput. 18(2): 982-993 (2021) - [c17]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: 3853-3866 - [c16]Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang:
When Machine Unlearning Jeopardizes Privacy. CCS 2021: 896-911 - [c15]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: 1237-1253 - [c14]Zitao Li, Trung Dang, Tianhao Wang, Ninghui Li:
MGD: A Utility Metric for Private Data Publication. NSysS 2021: 106-119 - [c13]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: 929-946 - [i16]Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang:
Graph Unlearning. CoRR abs/2103.14991 (2021) - [i15]Xiang Yue, Minxin Du, Tianhao Wang, Yaliang Li, Huan Sun, Sherman S. M. Chow:
Differential Privacy for Text Analytics via Natural Text Sanitization. CoRR abs/2106.01221 (2021) - [i14]Ninghui Li, Zhikun Zhang, Tianhao Wang:
DPSyn: Experiences in the NIST Differential Privacy Data Synthesis Challenges. CoRR abs/2106.12949 (2021) - [i13]Mingxun Zhou, Tianhao Wang, T.-H. Hubert Chan, Giulia Fanti, Elaine Shi:
Locally Differentially Private Sparse Vector Aggregation. CoRR abs/2112.03449 (2021) - 2020
- [j4]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): 2760-2772 (2020) - [j3]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): 3545-3558 (2020) - [j2]Jianyu Yang, Tianhao Wang, Ninghui Li, Xiang Cheng, Sen Su:
Answering Multi-Dimensional Range Queries under Local Differential Privacy. Proc. VLDB Endow. 14(3): 378-390 (2020) - [c12]Tianhao Wang, Milan Lopuhaä-Zwakenberg, Zitao Li, Boris Skoric, Ninghui Li:
Locally Differentially Private Frequency Estimation with Consistency. NDSS 2020 - [c11]Zitao Li, Tianhao Wang, Milan Lopuhaä-Zwakenberg, Ninghui Li, Boris Skoric:
Estimating Numerical Distributions under Local Differential Privacy. SIGMOD Conference 2020: 621-635 - [c10]Aiping Xiong, Tianhao Wang, Ninghui Li, Somesh Jha:
Towards Effective Differential Privacy Communication for Users' Data Sharing Decision and Comprehension. SP 2020: 392-410 - [i12]Aiping Xiong, Tianhao Wang, Ninghui Li, Somesh Jha:
Towards Effective Differential Privacy Communication for Users' Data Sharing Decision and Comprehension. CoRR abs/2003.13922 (2020) - [i11]Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang:
When Machine Unlearning Jeopardizes Privacy. CoRR abs/2005.02205 (2020) - [i10]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 abs/2005.11753 (2020) - [i9]Jianyu Yang, Tianhao Wang, Ninghui Li, Xiang Cheng, Sen Su:
Answering Multi-Dimensional Range Queries under Local Differential Privacy. CoRR abs/2009.06538 (2020) - [i8]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 abs/2012.09520 (2020) - [i7]Zhikun Zhang, Tianhao Wang, Ninghui Li, Jean Honorio, Michael Backes, Shibo He, Jiming Chen, Yang Zhang:
PrivSyn: Differentially Private Data Synthesis. CoRR abs/2012.15128 (2020)
2010 – 2019
- 2019
- [j1]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): 1862-1865 (2019) - [c9]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: 270-285 - [c8]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: 159-176 - [i6]Tianhao Wang, Zitao Li, Ninghui Li, Milan Lopuhaä-Zwakenberg, Boris Skoric:
Consistent and Accurate Frequency Oracles under Local Differential Privacy. CoRR abs/1905.08320 (2019) - [i5]Tianhao Wang, Min Xu, Bolin Ding, Jingren Zhou, Ninghui Li, Somesh Jha:
Practical and Robust Privacy Amplification with Multi-Party Differential Privacy. CoRR abs/1908.11515 (2019) - [i4]Zitao Li, Tianhao Wang, Milan Lopuhaä-Zwakenberg, Boris Skoric, Ninghui Li:
Estimating Numerical Distributions under Local Differential Privacy. CoRR abs/1912.01051 (2019) - 2018
- [c7]Zhikun Zhang, Tianhao Wang, Ninghui Li, Shibo He, Jiming Chen:
CALM: Consistent Adaptive Local Marginal for Marginal Release under Local Differential Privacy. CCS 2018: 212-229 - [c6]Graham Cormode, Somesh Jha, Tejas Kulkarni, Ninghui Li, Divesh Srivastava, Tianhao Wang:
Privacy at Scale: Local Differential Privacy in Practice. SIGMOD Conference 2018: 1655-1658 - [c5]Tianhao Wang, Ninghui Li, Somesh Jha:
Locally Differentially Private Frequent Itemset Mining. IEEE Symposium on Security and Privacy 2018: 127-143 - 2017
- [c4]Tianhao Wang, Jeremiah Blocki, Ninghui Li, Somesh Jha:
Locally Differentially Private Protocols for Frequency Estimation. USENIX Security Symposium 2017: 729-745 - [i3]Tianhao Wang, Jeremiah Blocki, Ninghui Li, Somesh Jha:
Optimizing Locally Differentially Private Protocols. CoRR abs/1705.04421 (2017) - [i2]Tianhao Wang, Ninghui Li, Somesh Jha:
Locally Differentially Private Heavy Hitter Identification. CoRR abs/1708.06674 (2017) - 2016
- [c3]Tianhao Wang, Yunlei Zhao:
Secure Dynamic SSE via Access Indistinguishable Storage. AsiaCCS 2016: 535-546 - [c2]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: 603-615 - 2015
- [i1]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 abs/1511.04123 (2015) - 2014
- [c1]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: 436
Coauthor Index
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