プライバシー保護

Diffprivlib: The IBM Differential Privacy Library

Authors: Naoise Holohan, Stefano Braghin, Pól Mac Aonghusa, Killian Levacher | Published: 2019-07-04
プライバシー保護
ライブラリ分類
機械学習フレームワーク

Capacity Bounded Differential Privacy

Authors: Kamalika Chaudhuri, Jacob Imola, Ashwin Machanavajjhala | Published: 2019-07-03
プライバシー保護
情報収集手法
研究方法論

Protecting Privacy of Users in Brain-Computer Interface Applications

Authors: Anisha Agarwal, Rafael Dowsley, Nicholas D. McKinney, Dongrui Wu, Chin-Teng Lin, Martine De Cock, Anderson C. A. Nascimento | Published: 2019-07-02
セキュアなロジスティック回帰
プライバシー保護
機械学習フレームワーク

DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM

Authors: Bao Wang, Quanquan Gu, March Boedihardjo, Farzin Barekat, Stanley J. Osher | Published: 2019-06-28 | Updated: 2019-12-07
プライバシー保護
最適化戦略
機械学習フレームワーク

Secure Summation via Subset Sums: A New Primitive for Privacy-Preserving Distributed Machine Learning

Authors: Valentin Hartmann, Robert West | Published: 2019-06-27 | Updated: 2023-06-19
データ抽出と分析
プライバシー保護
初期シード生成

Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference

Authors: Klas Leino, Matt Fredrikson | Published: 2019-06-27 | Updated: 2020-06-24
プライバシー保護
メンバーシップ推論
敵対的攻撃

The Cost of a Reductions Approach to Private Fair Optimization

Authors: Daniel Alabi | Published: 2019-06-23 | Updated: 2021-05-23
アルゴリズム設計
プライバシー保護
最適化戦略

Deep Leakage from Gradients

Authors: Ligeng Zhu, Zhijian Liu, Song Han | Published: 2019-06-21 | Updated: 2019-12-19
プライバシー保護
敵対的攻撃
防御的欺瞞

Scalable and Differentially Private Distributed Aggregation in the Shuffled Model

Authors: Badih Ghazi, Rasmus Pagh, Ameya Velingker | Published: 2019-06-19 | Updated: 2019-12-02
データ抽出と分析
プライバシー保護
連合学習

Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation

Authors: Han Zhao, Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon | Published: 2019-06-19 | Updated: 2020-10-25
プライバシー保護
メンバーシップ推論
最適化問題