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Side-channel attack (SCA) has shown to be a serious implementation attack to many cryptosystems. Practical countermeasures only mitigate the vulnerability to some extent. Considerable research efforts on leakage-resilient cryptography have so far not led to practical leakage-resilient implementations. One hindering reason is the lack of commonly accepted and sound metrics, standards, and evaluation procedures to measure and evaluate the vulnerability/resilience of cryptosystems to various side-channel attacks. Accurate modeling of side channels, however, is one of the open problems in applied crypto research. This project aims to close the gap between SCA theories and practices by formalizing a general framework for side-channel attack analysis and security evaluation of cryptosystems.
The proposed framework quantifies the effect of algorithmic and implementation characteristics on the success rate of the theoretically strongest maximum likelihood attack, revealing system-inherent SCA-related parameters for security improvement. The framework will extract maximum leakage from the observed measurement data in the black-box scenario, often the realistic situation for adversaries. State-of-the-art statistical methods are employed in the framework to precisely analyze and evaluate the overall side-channel leakage. This holistic framework will significantly alleviate the burden of security system architects, software developers, and hardware designers in their quest to build SCA security into systems they design, so as to ultimately yield provably secure hardware.
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TWC: Medium: Collaborative: A Unified Statistics-Based Framework for Side-Channel Attack Analysis and Security Evaluation of Cryptosystems