There have been many attacks that exploit side-effects of program execution to expose secret information and many proposed countermeasures to protect against these attacks. However there is currently no systematic, holistic methodology for understanding information leakage. As a result, it is not well known how design decisions affect information leakage or the vulnerability of systems to side-channel attacks.In this paper, we propose a metric for measuring information leakage called the Side-channel Vulnerability Factor (SVF). SVF is based on our observation that all sidechannel attacks ranging from physical to microarchitectural to software rely on recognizing leaked execution patterns. SVF quantifies patterns in attackers' observations and measures their correlation to the victim's actual execution patterns and in doing so captures systems' vulnerability to side-channel attacks.In a detailed case study of on-chip memory systems, SVF measurements help expose unexpected vulnerabilities in whole-system designs and shows how designers can make performance-security trade-offs. Thus, SVF provides a quantitative approach to secure computer architecture.
Over the past two decades, several microarchitectural side channels have been exploited to create sophisticated security attacks. Solutions to this problem have mainly focused on fixing the source of leaks either by limiting the flow of information through the side channel by modifying hardware, or by refactoring vulnerable software to protect sensitive data from leaking. These solutions are reactive and not preventative: while the modifications may protect against a single attack, they do nothing to prevent future side channel attacks that exploit other microarchitectural side channels or exploit the same side channel in a novel way.In this paper we present a general mitigation strategy that focuses on the infrastructure used to measure side channel leaks rather than the source of leaks, and thus applies to all known and unknown microarchitectural side channel leaks. Our approach is to limit the fidelity of fine grain timekeeping and performance counters, making it difficult for an attacker to distinguish between different microarchitectural events, thus thwarting attacks. We demonstrate the strength of our proposed security modifications, and validate that our changes do not break existing software. Our proposed changes require minor -or in some cases, no -hardware modifications and do not result in any substantial performance degradation, yet offer the most comprehensive protection against microarchitectural side channels to date.
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