Differentially Private Coordinate Descent for Composite Empirical Risk Minimization
Authors: Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi | Published: 2021-10-22 | Updated: 2022-10-21
プライバシー保護
PRECAD: Privacy-Preserving and Robust Federated Learning via Crypto-Aided Differential Privacy
Authors: Xiaolan Gu, Ming Li, Li Xiong | Published: 2021-10-22
Privacy in Open Search: A Review of Challenges and Solutions
Authors: Samuel Sousa, Christian Guetl, Roman Kern | Published: 2021-10-20 | Updated: 2022-04-04
GALA: Greedy ComputAtion for Linear Algebra in Privacy-Preserved Neural Networks
Authors: Qiao Zhang, Chunsheng Xin, Hongyi Wu | Published: 2021-05-05
Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX
Authors: Chengliang Zhang, Junzhe Xia, Baichen Yang, Huancheng Puyang, Wei Wang, Ruichuan Chen, Istemi Ekin Akkus, Paarijaat Aditya, Feng Yan | Published: 2021-05-04 | Updated: 2021-11-08
Quantifying the Tradeoff Between Cybersecurity and Location Privacy
Authors: Dajiang Suo, M. Elena Renda, Jinhua Zhao | Published: 2021-05-04 | Updated: 2021-12-10
AirMixML: Over-the-Air Data Mixup for Inherently Privacy-Preserving Edge Machine Learning
Authors: Yusuke Koda, Jihong Park, Mehdi Bennis, Praneeth Vepakomma, Ramesh Raskar | Published: 2021-05-02
Privacy and Integrity Preserving Training Using Trusted Hardware
Authors: Hanieh Hashemi, Yongqin Wang, Murali Annavaram | Published: 2021-05-01
Improved Matrix Gaussian Mechanism for Differential Privacy
Authors: Jungang Yang, Liyao Xiang, Weiting Li, Wei Liu, Xinbing Wang | Published: 2021-04-30
Property Inference Attacks on Convolutional Neural Networks: Influence and Implications of Target Model’s Complexity
Authors: Mathias P. M. Parisot, Balazs Pejo, Dayana Spagnuelo | Published: 2021-04-27