Privacy Preserving and Collusion Resistant Energy Sharing. - Yuan Hong 001; Han Wang 021; Shangyu Xie; Bingyu Liu (ICASSP, 2018)

Homogeneous and Mixed Energy Communities Discovery with Spatial-Temporal Net Energy. - Shangyu Xie; Han Wang 021; Shengbin Wang; Haibing Lu; Yuan Hong 001; Dong Jin; Qi Liu (CoRR, 2019)

VideoDP: A Universal Platform for Video Analytics with Differential Privacy. - Han Wang 021; Shangyu Xie; Yuan Hong 001 (CoRR, 2019)

Publishing Video Data with Indistinguishable Objects. - Han Wang 021; Yuan Hong 001; Yu Kong 001; Jaideep Vaidya (EDBT, 2020)

Privacy Preserving Distributed Energy Trading. - Shangyu Xie; Han Wang 021; Yuan Hong 001; My Thai (ICDCS, 2020)

VideoDP: A Flexible Platform for Video Analytics with Differential Privacy. - Han Wang 021; Shangyu Xie; Yuan Hong 001 (Proc. Priv. Enhancing Technol., 2020)

VTDP: Privately Sanitizing Fine-Grained Vehicle Trajectory Data With Boosted Utility. - Bingyu Liu; Shangyu Xie; Han Wang 021; Yuan Hong 001; Xuegang Ban; Meisam Mohammady (IEEE Trans. Dependable Secur. Comput., 2021)

L-SRR: Local Differential Privacy for Location-Based Services with Staircase Randomized Response. - Han Wang 021; Hanbin Hong; Li Xiong 001; Zhan Qin; Yuan Hong 001 (CCS, 2022)

A Generalized Framework for Preserving Both Privacy and Utility in Data Outsourcing (Extended Abstract). - Shangyu Xie; Meisam Mohammady; Han Wang 021; Lingyu Wang 001; Jaideep Vaidya; Yuan Hong 001 (ICDE, 2022)

A Model-Agnostic Approach to Differentially Private Topic Mining. - Han Wang 021; Jayashree Sharma; Shuya Feng; Kai Shu; Yuan Hong 001 (KDD, 2022)

Universal 3-Dimensional Perturbations for Black-Box Attacks on Video Recognition Systems. - Shangyu Xie; Han Wang 021; Yu Kong 001; Yuan Hong 001 (SP, 2022)

DPOAD: Differentially Private Outsourcing of Anomaly Detection through Iterative Sensitivity Learning. - Meisam Mohammady; Han Wang 021; Lingyu Wang 001; Mengyuan Zhang 001; Yosr Jarraya; Suryadipta Majumdar; Makan Pourzandi; Mourad Debbabi; Yuan Hong 001 (CoRR, 2022)

A Generalized Framework for Preserving Both Privacy and Utility in Data Outsourcing. - Shangyu Xie; Meisam Mohammady; Han Wang 021; Lingyu Wang 001; Jaideep Vaidya; Yuan Hong 001 (IEEE Trans. Knowl. Data Eng., 2023)

Towards Accurate and Stronger Local Differential Privacy for Federated Learning with Staircase Randomized Response. - Matta Varun; Shuya Feng; Han Wang 021; Shamik Sural; Yuan Hong 001 (CODASPY, 2024)

DPI: Ensuring Strict Differential Privacy for Infinite Data Streaming. - Shuya Feng; Meisam Mohammady; Han Wang 021; Xiaochen Li; Zhan Qin; Yuan Hong 001 (SP, 2024)

LMO-DP: Optimizing the Randomization Mechanism for Differentially Private Fine-Tuning (Large) Language Models. - Qin Yang; Meisam Mohammady; Han Wang 021; Ali Payani; Ashish Kundu; Kai Shu; Yan Yan 002; Yuan Hong 001 (CoRR, 2024)

Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning. - Nexhi Sula; Abhinav Kumar; Jie Hou 001; Han Wang 021; Reza Tourani (CoRR, 2024)

ASDIA: An Adversarial Sample to Preserve Privacy Program in Federated Learning. - Shujuan Tian; Yi Tan; Han Wang 021; Haolin Liu; Zhetao Li (IEEE Trans. Dependable Secur. Comput., 2025)