Flatee: Federated Learning Across Trusted Execution Environments
Authors: Arup Mondal, Yash More, Ruthu Hulikal Rooparaghunath, Debayan Gupta | Published: 2021-11-12
Privacy Protection
Secure Machine Learning in the Cloud Using One Way Scrambling by Deconvolution
Authors: Yiftach Savransky, Roni Mateless, Gilad Katz | Published: 2021-11-04
A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection
Authors: Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marius Portmann | Published: 2021-11-04
DP-XGBoost: Private Machine Learning at Scale
Authors: Nicolas Grislain, Joan Gonzalvez | Published: 2021-10-25
Addressing Privacy Threats from Machine Learning
Authors: Mary Anne Smart | Published: 2021-10-25
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
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