Defense Against Gradient Leakage Attacks via Learning to Obscure Data
Authors: Yuxuan Wan, Han Xu, Xiaorui Liu, Jie Ren, Wenqi Fan, Jiliang Tang | Published: 2022-06-01
プライバシー評価
Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data
Authors: Huancheng Chen, Haris Vikalo | Published: 2022-06-01 | Updated: 2023-04-20
Differentially Private Shapley Values for Data Evaluation
Authors: Lauren Watson, Rayna Andreeva, Hao-Tsung Yang, Rik Sarkar | Published: 2022-06-01
Privacy for Free: How does Dataset Condensation Help Privacy?
Authors: Tian Dong, Bo Zhao, Lingjuan Lyu | Published: 2022-06-01
Private Federated Submodel Learning with Sparsification
Authors: Sajani Vithana, Sennur Ulukus | Published: 2022-05-31
A Blessing of Dimensionality in Membership Inference through Regularization
Authors: Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk | Published: 2022-05-27 | Updated: 2023-04-14
Auditing Differential Privacy in High Dimensions with the Kernel Quantum Rényi Divergence
Authors: Carles Domingo-Enrich, Youssef Mroueh | Published: 2022-05-27
Additive Logistic Mechanism for Privacy-Preserving Self-Supervised Learning
Authors: Yunhao Yang, Parham Gohari, Ufuk Topcu | Published: 2022-05-25
On the Importance of Architecture and Feature Selection in Differentially Private Machine Learning
Authors: Wenxuan Bao, Luke A. Bauer, Vincent Bindschaedler | Published: 2022-05-13
Collaborative Drug Discovery: Inference-level Data Protection Perspective
Authors: Balazs Pejo, Mina Remeli, Adam Arany, Mathieu Galtier, Gergely Acs | Published: 2022-05-13 | Updated: 2022-06-09