Our paper “Privacy for Free: Leveraging Local Differential Privacy Perturbed Data from Multiple Services” is accepted by The Proceedings of the VLDB Endowment (PVLDB), 2025.

Our papers “MER-Inspector: Assessing Model Extraction Risks from An Attack-Agnostic Perspective” and “FUNU: Boosting Machine Unlearning Efficiency by Filtering Unnecessary Unlearning” are accepted by ACM TheWebConf 2025 (WWW 2025).

Our papers “A Sample-Level Evaluation and Generative Framework for Model Inversion Attacks” and “Exploring Intrinsic Alignments within Text Corpus” are accepted by Annual AAAI Conference on Artificial Intelligence (AAAI 2025).

Our papers “Structure-Preference Enabled Graph Embedding Generation under Differential Privacy” and “Data Poisoning Attacks to Local Differential Privacy Protocols for Graphs” are accepted by IEEE International Conference on Data Engineering (ICDE), 2025.

Our paper “PrivDPR: Synthetic Graph Publishing with Deep PageRank under Differential Privacy” is accepted by SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025).

Our paper “Federated Heavy Hitter Analytics with Local Differential Privacy” is accepted by International Conference of Management of Data (SIGMOD 2025)”. Our paper “Membership Inference Attacks and Defenses in Federated Learning: A Survey” is accepted by ACM Computing Surveys.