12 citations · 12 across the 3 of their papers we have counts for
4 papers
KV-Auditor: Auditing Local Differential Privacy for Correlated Key-Value Estimation
Jingnan Xu, Leixia Wang, Xiaofeng Meng
To protect privacy for data-collection-based services, local differential privacy (LDP) is widely adopted due to its rigorous theoretical bound on privacy loss. However, mistakes i…
Membership Inference Attacks and Defenses in Federated Learning: A Survey
Li Bai, Haibo Hu, Qingqing Ye +3
Federated learning is a decentralized machine learning approach where clients train models locally and share model updates to develop a global model. This enables low-resource devi…
PriPL-Tree: Accurate Range Query for Arbitrary Distribution under Local Differential Privacy
Leixia Wang, Qingqing Ye, Haibo Hu +1
Answering range queries in the context of Local Differential Privacy (LDP) is a widely studied problem in Online Analytical Processing (OLAP). Existing LDP solutions all assume a u…
Differentially Private Federated Learning: A Systematic Review
Jie Fu, Yuan Hong, Xinpeng Ling +6
In recent years, privacy and security concerns in machine learning have promoted trusted federated learning to the forefront of research. Differential privacy has emerged as the de…