Analyzing cache side channels using deep neural networks

Tianwei Zhang, Yinqian Zhang, Ruby B. Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Cache side-channel attacks aim to breach the confidentiality of a computer system and extract sensitive secrets through CPU caches. In the past years, different types of side-channel attacks targeting a variety of cache architectures have been demonstrated. Meanwhile, different defense methods and systems have also been designed to mitigate these attacks. However, quantitatively evaluating the effectiveness of these attacks and defenses has been challenging. We propose a generic approach to evaluating cache side-channel attacks and defenses. Specifically, our method builds a deep neural network with its inputs as the adversary's observed information, and its outputs as the victim's execution traces. By training the neural network, the relationship between the inputs and outputs can be automatically discovered. As a result, the prediction accuracy of the neural network can serve as a metric to quantify how much information the adversary can obtain correctly, and how effective a defense solution is in reducing the information leakage under different attack scenarios. Our evaluation suggests that the proposed method can effectively evaluate different attacks and defenses.

Original languageEnglish (US)
Title of host publicationACM International Conference Proceeding Series
PublisherAssociation for Computing Machinery
Pages174-186
Number of pages13
ISBN (Electronic)9781450365697
DOIs
StatePublished - Dec 3 2018
Event34th Annual Computer Security Applications Conference, ACSAC 2018 - San Juan, United States
Duration: Dec 3 2018Dec 7 2018

Publication series

NameACM International Conference Proceeding Series

Other

Other34th Annual Computer Security Applications Conference, ACSAC 2018
CountryUnited States
CitySan Juan
Period12/3/1812/7/18

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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  • Cite this

    Zhang, T., Zhang, Y., & Lee, R. B. (2018). Analyzing cache side channels using deep neural networks. In ACM International Conference Proceeding Series (pp. 174-186). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3274694.3274715