Data Poisoning Attacks Against Federated Learning Systems-Reference-Cited by-同舟云学术

Data Poisoning Attacks Against Federated Learning Systems

Published:2020 Issue: Volume: Page:480-501
ISSN:0302-9743
Container-title:Computer Security – ESORICS 2020
language:
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Author:

Tolpegin Vale,Truex Stacey,Gursoy Mehmet Emre,Liu Ling

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-58951-6_24

Reference59 articles.

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3. Baracaldo, N., Chen, B., Ludwig, H., Safavi, J.A.: Mitigating poisoning attacks on machine learning models: a data provenance based approach. In: 10th ACM Workshop on Artificial Intelligence and Security, pp. 103–110 (2017)

4. 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)

5. Biggio, B., Nelson, B., Laskov, P.: Support vector machines under adversarial label noise. In: Asian Conference on Machine Learning, pp. 97–112 (2011)

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