Identifying Security Critical Properties for the Dynamic Verification of a Processor
Rui Zhang, Natalie Stanley, Christopher Griggs, Andrew Chi, Cynthia Sturton · 2017
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.