A Quantitative, Experimental Approach to Measuring Processor Side-Channel Security

User inputs tend to change the execution characteristics of applications including their interactions with cache, network, storage, and other systems. Many attacks have exploited the observable side effects of these execution characteristics to expose sensitive information. In response, researchers...

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Bibliographic Details
Published in:IEEE MICRO 2013-05, Vol.33 (3), p.68-77
Main Authors: Demme, J., Martin, R., Waksman, A., Sethumadhavan, S.
Format: Article
Language:English
Subjects:
Architecture (computers)
Computer architecture
Computer information security
Correlation analysis
Cybersecurity
data
data encryption
Data models
Design engineering
Encryption
hardware
Information
Information technology
information technology and systems
integration
Leakage
Memory management
memory structures
Microarchitecture
Microprocessors
modeling
models and principles
Pattern recognition
Recognition
Side effects
Software
System performance
systems and information theory
systems architecture
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Summary:User inputs tend to change the execution characteristics of applications including their interactions with cache, network, storage, and other systems. Many attacks have exploited the observable side effects of these execution characteristics to expose sensitive information. In response, researchers have 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 entire systems to side-channel attacks. The authors propose a metric for measuring information leakage called the Side-channel Vulnerability Factor (SVF). The SVF is based on the observation that all side-channel attacks - ranging from physical to microarchitectural to software - rely on recognizing leaked execution patterns. The SVF quantifies patterns in attackers' observations and measures their correlation to the victim's actual execution patterns and in doing so captures systems' predisposition to leak information. Thus, the SVF provides a quantitative approach to securing computer architecture.
ISSN:0272-1732
1937-4143
DOI:10.1109/MM.2013.23