Fall of empires: Breaking byzantine-tolerant SGD by inner product manipulation

Research output: Contribution to conferencePaperpeer-review

Abstract

Recently, new defense techniques have been developed to tolerate Byzantine failures for distributed machine learning. The Byzantine model captures workers that behave arbitrarily, including malicious and compromised workers. In this paper, we break two prevailing Byzantine-tolerant techniques. Specifically we show that two robust aggregation methods for synchronous SGD–namely, coordinate-wise median and Krum–can be broken using new attack strategies based on inner product manipulation. We prove our results theoretically, as well as show empirical validation.

Original languageEnglish (US)
StatePublished - 2019
Event35th Conference on Uncertainty in Artificial Intelligence, UAI 2019 - Tel Aviv, Israel
Duration: Jul 22 2019Jul 25 2019

Conference

Conference35th Conference on Uncertainty in Artificial Intelligence, UAI 2019
CountryIsrael
CityTel Aviv
Period7/22/197/25/19

ASJC Scopus subject areas

  • Artificial Intelligence

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