Mitigating Poisoning Attack in Federated Learning-Reference-Cited by-同舟云学术

Mitigating Poisoning Attack in Federated Learning

Published:2021-12-05 Issue: Volume: Page:
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Container-title:2021 IEEE Symposium Series on Computational Intelligence (SSCI)
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Author:

Uprety Aashma,Rawat Danda B.

Funder

U.S. NSF

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9659537/9659538/09659839.pdf?arnumber=9659839

Reference22 articles.

1. Towards poisoning of deep learning algorithms with back-gradient optimization;muñoz-gonzález;Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security,0

2. Poison frogs! targeted clean-label poisoning attacks on neural networks;shafahi;ArXiv Preprint,2018

3. The modeling and implementation of Non- rigid motion based on the carcass traits

4. Auror: Defending against poisoning attacks in collaborative deep learning systems;shen;Proceedings of the 32nd Annual Conference on Computer Security Applications,0

5. A little is enough: Circumventing defenses for distributed learning;baruch;ArXiv Preprint,2019

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