Mitigating Distributed Backdoor Attack in Federated Learning Through Mode Connectivity

Author:

Walter Kane1ORCID,Mohammady Meisam2ORCID,Nepal Surya3ORCID,Kanhere Salil S.1ORCID

Affiliation:

1. UNSW, Sydney, Australia

2. Iowa State University of Science and Technology, Iowa, USA

3. Data61, CSIRO, Sydney, Australia

Publisher

ACM

Reference38 articles.

1. [n. d.]. Machine Learning Ledger Orchestration For Drug Discovery (MEL-LODDY). [Online]. Available: https://www.melloddy.eu/.

2. [n. d.]. Utilization of FATE in Risk Management of Credit in Small and Micro Enterprises. [Online]. Available: ttps://www.fedai.org/cases/utilization-of-fate-in-risk-management-of-credit-in-small-and-micro-enterprises/.

3. BaFFLe: Backdoor Detection via Feedback-based Federated Learning

4. Peter Auer, Mark Herbster, and Manfred K. Warmuth. 1995. Exponentially many local minima for single neurons. In Advances in Neural Information Processing Systems 8, NIPS, Denver, CO, USA, November 27-30, 1995, David S. Touretzky, Michael Mozer, and Michael E. Hasselmo (Eds.). MIT Press, 316--322.

5. Eugene Bagdasaryan, Andreas Veit, Yiqing Hua, Deborah Estrin, and Vitaly Shmatikov. 2020. How To Backdoor Federated Learning. In Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics (Proceedings of Machine Learning Research, Vol. 108), Silvia Chiappa and Roberto Calandra (Eds.). PMLR, 2938--2948.

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