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Symbolic Predictive Cache Analysis for Out-of-Order Execution

Authors: Zunchen Huang; Chao Wang 0001;

Symbolic Predictive Cache Analysis for Out-of-Order Execution

Abstract

AbstractWe propose a trace-based symbolic method for analyzing cache side channels of a program under a CPU-level optimization called out-of-order execution (OOE). The method is predictive in that it takes the in-order execution trace as input and then analyzes all possible out-of-order executions of the same set of instructions to check if any of them leaks sensitive information of the program. The method has two important properties. The first one is accurately analyzing cache behaviors of the program execution under OOE, which is largely overlooked by existing methods for side-channel verification. The second one is efficiently analyzing the cache behaviors using an SMT solver based symbolic technique, to avoid explicitly enumerating a large number of out-of-order executions. Our experimental evaluation on C programs that implement cryptographic algorithms shows that the symbolic method is effective in detecting OOE-related leaks and, at the same time, is significantly more scalable than explicit enumeration.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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