ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing

8 June 2020

Papers citing "ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing"

6 / 6 papers shown

Title
Training Large Scale Polynomial CNNs for E2E Inference over Homomorphic Encryption Moran Baruch Nir Drucker Gilad Ezov Yoav Goldberg Eyal Kushnir Jenny Lerner Omri Soceanu Itamar Zimerman 49 6 0 26 Apr 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 84 47 0 21 Feb 2023
Secret Sharing Sharing For Highly Scalable Secure Aggregation Timothy Stevens Joseph P. Near Christian Skalka FedML 16 5 0 03 Jan 2022
Privacy-preserving medical image analysis Alexander Ziller Jonathan Passerat-Palmbach T. Ryffel Dmitrii Usynin Andrew Trask ... Jason V. Mancuso Marcus R. Makowski Daniel Rueckert R. Braren Georgios Kaissis 21 8 0 10 Dec 2020
SPEED: Secure, PrivatE, and Efficient Deep learning Arnaud Grivet Sébert Rafael Pinot Martin Zuber Cédric Gouy-Pailler Renaud Sirdey FedML 11 20 0 16 Jun 2020
CrypTFlow: Secure TensorFlow Inference Nishant Kumar Mayank Rathee Nishanth Chandran Divya Gupta Aseem Rastogi Rahul Sharma 96 235 0 16 Sep 2019