Can You Really Backdoor Federated Learning?

18 November 2019

Papers citing "Can You Really Backdoor Federated Learning?"

7 / 107 papers shown

Title
Federated Learning Meets Multi-objective Optimization Zeou Hu Kiarash Shaloudegi Guojun Zhang Yaoliang Yu FedML 23 89 0 20 Jun 2020
Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training? Sharif Abuadbba Kyuyeon Kim Minki Kim Chandra Thapa S. Çamtepe Yansong Gao Hyoungshick Kim Surya Nepal FedML 8 123 0 16 Mar 2020
NNoculation: Catching BadNets in the Wild A. Veldanda Kang Liu Benjamin Tan Prashanth Krishnamurthy Farshad Khorrami Ramesh Karri Brendan Dolan-Gavitt S. Garg AAML OnRL 19 20 0 19 Feb 2020
Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning Jinhyun So Başak Güler A. Avestimehr FedML 34 289 0 11 Feb 2020
Learning to Detect Malicious Clients for Robust Federated Learning Suyi Li Yong Cheng Wei Wang Yang Liu Tianjian Chen AAML FedML 21 224 0 01 Feb 2020
Robust Aggregation for Federated Learning Krishna Pillutla Sham Kakade Zaïd Harchaoui FedML 42 632 0 31 Dec 2019
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 191 1,034 0 29 Nov 2018