POSEIDON: Privacy-Preserving Federated Neural Network Learning

POSEIDON: Privacy-Preserving Federated Neural Network Learning

1 September 2020

Apostolos Pyrgelis

J. Troncoso-Pastoriza

Jean-Philippe Bossuat

João Sá Sousa

Jean-Pierre Hubaux

Papers citing "POSEIDON: Privacy-Preserving Federated Neural Network Learning"

18 / 18 papers shown

Title
Arbitrary-Threshold Fully Homomorphic Encryption with Lower Complexity Yijia Chang Songze Li 48 0 0 20 Jan 2025
TETRIS: Composing FHE Techniques for Private Functional Exploration Over Large Datasets Malika Izabachène Jean-Philippe Bossuat 86 0 0 17 Dec 2024
Secure Outsourced Decryption for FHE-based Privacy-preserving Cloud Computing Xirong Ma Chuan Li Yuchang Hu Yunting Tao Yali Jiang Yanbin Li Fanyu Kong Chunpeng Ge 56 0 0 28 Jun 2024
Privacy-Preserving Federated Unlearning with Certified Client Removal Ziyao Liu Huanyi Ye Yu Jiang Jiyuan Shen Jiale Guo Ivan Tjuawinata Kwok-Yan Lam MU 40 5 0 15 Apr 2024
Federated learning with differential privacy and an untrusted aggregator Kunlong Liu Trinabh Gupta 55 0 0 17 Dec 2023
FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks Jorge Castillo Phillip Rieger Hossein Fereidooni Qian Chen Ahmad Sadeghi FedML AAML 41 8 0 03 Oct 2023
A Survey for Federated Learning Evaluations: Goals and Measures Di Chai Leye Wang Liu Yang Junxue Zhang Kai Chen Qian Yang ELM FedML 27 21 0 23 Aug 2023
Privacy-Preserving 3-Layer Neural Network Training Jonathan Z. Chiang 24 5 0 18 Aug 2023
Scalable and Privacy-Preserving Federated Principal Component Analysis D. Froelicher Hyunghoon Cho Manaswitha Edupalli João Sá Sousa Jean-Philippe Bossuat Apostolos Pyrgelis J. Troncoso-Pastoriza Bonnie Berger Jean-Pierre Hubaux FedML 24 15 0 31 Mar 2023
SoK: Fully Homomorphic Encryption Accelerators Junxue Zhang Xiaodian Cheng Liu Yang Jinbin Hu Ximeng Liu Kai Chen 34 23 0 04 Dec 2022
Privacy-preserving Decentralized Federated Learning over Time-varying Communication Graph Yang Lu Zhengxin Yu N. Suri FedML 31 14 0 01 Oct 2022
Orchestrating Collaborative Cybersecurity: A Secure Framework for Distributed Privacy-Preserving Threat Intelligence Sharing J. Troncoso-Pastoriza Alain Mermoud Romain Bouyé Francesco Marino Jean-Philippe Bossuat Vincent Lenders Jean-Pierre Hubaux 37 3 0 06 Sep 2022
Verifiable Encodings for Secure Homomorphic Analytics Sylvain Chatel Christian Knabenhans Apostolos Pyrgelis Carmela Troncoso Jean-Pierre Hubaux 33 19 0 28 Jul 2022
Hercules: Boosting the Performance of Privacy-preserving Federated Learning Guowen Xu Xingshuo Han Shengmin Xu Tianwei Zhang Hongwei Li Xinyi Huang R. Deng FedML 37 16 0 11 Jul 2022
SCOTCH: An Efficient Secure Computation Framework for Secure Aggregation Yash More Prashanthi Ramachandran Priyam Panda A. Mondal Harpreet Virk Debayan Gupta FedML 29 11 0 19 Jan 2022
Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption Dimitris Stripelis Hamza Saleem Tanmay Ghai Nikhil J. Dhinagar Umang Gupta ... Greg Ver Steeg Yu Yang Muhammad Naveed Paul M. Thompson J. Ambite FedML 48 53 0 07 Aug 2021
Encrypted Distributed Lasso for Sparse Data Predictive Control A. Alexandru Anastasios Tsiamis George J. Pappas 17 10 0 23 Apr 2021
Revolutionizing Medical Data Sharing Using Advanced Privacy Enhancing Technologies: Technical, Legal and Ethical Synthesis J. Scheibner J. Raisaro J. Troncoso-Pastoriza M. Ienca J. Fellay E. Vayena Jean-Pierre Hubaux 18 75 0 27 Oct 2020