3 papers
cs.CR2025
Toward Efficient Inference Attacks: Shadow Model Sharing via Mixture-of-Experts
Li Bai, Qingqing Ye, Xinwei Zhang +4
Machine learning models are often vulnerable to inference attacks that expose sensitive information from their training data. Shadow model technique is commonly employed in such at…
stat.ML2025
Structure-Preference Enabled Graph Embedding Generation under Differential Privacy
Sen Zhang, Qingqing Ye, Haibo Hu
Graph embedding generation techniques aim to learn low-dimensional vectors for each node in a graph and have recently gained increasing research attention. Publishing low-dimension…
cs.DB2025
PrivDPR: Synthetic Graph Publishing with Deep PageRank under Differential Privacy
Sen Zhang, Haibo Hu, Qingqing Ye +1
The objective of privacy-preserving synthetic graph publishing is to safeguard individuals' privacy while retaining the utility of original data. Most existing methods focus on gra…