Identifying Security Critical Properties for the Dynamic Verification of a Processor
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Published:2017-05-11
Issue:1
Volume:45
Page:541-554
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ISSN:0163-5964
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Container-title:ACM SIGARCH Computer Architecture News
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language:en
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Short-container-title:SIGARCH Comput. Archit. News
Author:
Zhang Rui1,
Stanley Natalie1,
Griggs Christopher1,
Chi Andrew1,
Sturton Cynthia1
Affiliation:
1. The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Abstract
We present a methodology for identifying security critical properties for use in the dynamic verification of a processor. Such verification has been shown to be an effective way to prevent exploits of vulnerabilities in the processor, given a meaningful set of security properties. We use known processor errata to establish an initial set of security-critical invariants of the processor. We then use machine learning to infer an additional set of invariants that are not tied to any particular, known vulnerability, yet are critical to security.
We build a tool chain implementing the approach and evaluate it for the open-source OR1200 RISC processor. We find that our tool can identify 19 (86.4%) of the 22 manually crafted security-critical properties from prior work and generates 3 new security properties not covered in prior work.
Funder
National Science Foundation
National Institutes of Health
Publisher
Association for Computing Machinery (ACM)
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