Romoa: Robust Model Aggregation for the Resistance of Federated Learning to Model Poisoning Attacks-Reference-Cited by-同舟云学术

Romoa: Robust Model Aggregation for the Resistance of Federated Learning to Model Poisoning Attacks

Published:2021 Issue: Volume: Page:476-496
ISSN:0302-9743
Container-title:Computer Security – ESORICS 2021
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Author:

Mao Yunlong,Yuan Xinyu,Zhao Xinyang,Zhong Sheng

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-88418-5_23

Reference40 articles.

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3. Bhagoji, A.N., Chakraborty, S., Mittal, P., Calo, S.: Analyzing federated learning through an adversarial lens. In: International Conference on Machine Learning, pp. 634–643 (2019)

4. Blanchard, P., El Mhamdi, E.M., Guerraoui, R., Stainer, J.: Machine learning with adversaries: byzantine tolerant gradient descent. In: Proceedings of the 31st International Conference on Neural Information Processing Systems, pp. 118–128 (2017)

5. Bonawitz, K., et al.: Practical secure aggregation for privacy-preserving machine learning. In: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, pp. 1175–1191 (2017)

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