EIFFeL: Ensuring Integrity for Federated Learning

EIFFeL: Ensuring Integrity for Federated Learning

23 December 2021

Laurens van der Maaten

Papers citing "EIFFeL: Ensuring Integrity for Federated Learning"

15 / 15 papers shown

Title
Efficient Full-Stack Private Federated Deep Learning with Post-Quantum Security Yiwei Zhang R. Behnia A. Yavuz Reza Ebrahimi E. Bertino FedML 61 0 0 09 May 2025
SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Zhihui Zhao Xiaorong Dong Yimo Ren Jianhua Wang Dan Yu Hongsong Zhu Yongle Chen 103 0 0 24 Feb 2025
TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning Runhua Xu Bo Li Chao Li J. Joshi Shuai Ma Jianxin Li FedML 66 10 0 10 Jan 2025
PriRoAgg: Achieving Robust Model Aggregation with Minimum Privacy Leakage for Federated Learning Sizai Hou Songze Li Tayyebeh Jahani-Nezhad Giuseppe Caire FedML 74 2 0 12 Jul 2024
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification Ashwinee Panda Saeed Mahloujifar A. Bhagoji Supriyo Chakraborty Prateek Mittal FedML AAML 24 85 0 12 Dec 2021
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks Chulin Xie Minghao Chen Pin-Yu Chen Yue Liu FedML 59 166 0 15 Jun 2021
Byzantine-Resilient Secure Federated Learning Jinhyun So Başak Güler A. Avestimehr FedML 34 239 0 21 Jul 2020
Learning to Detect Malicious Clients for Robust Federated Learning Suyi Li Yong Cheng Wei Wang Yang Liu Tianjian Chen AAML FedML 91 224 0 01 Feb 2020
The power of synergy in differential privacy: Combining a small curator with local randomizers A. Beimel Aleksandra Korolova Kobbi Nissim Or Sheffet Uri Stemmer 41 14 0 18 Dec 2019
Can You Really Backdoor Federated Learning? Ziteng Sun Peter Kairouz A. Suresh H. B. McMahan FedML 50 565 0 18 Nov 2019
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 70 2,652 0 04 Feb 2019
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 113 1,461 0 10 May 2018
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning Xinyun Chen Chang-rui Liu Yue Liu Kimberly Lu D. Song AAML SILM 64 1,822 0 15 Dec 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 253 4,620 0 18 Oct 2016
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 60 1,580 0 27 Jun 2012