Paper 2024/1735

The Mysteries of LRA: Roots and Progresses in Side-channel Applications

Abstract

Evaluation of cryptographic implementations with respect to side-channels has been mandated at high security levels nowadays. Typically, the evaluation involves four stages: detection, modeling, certification and secret recovery. In pursuit of specific goal at each stage, inherently different techniques used to be considered necessary. However, since the recent works of Eurocrypt2022 and Eurocrypt2024, linear regression analysis (LRA) has uniquely become the technique that is well-applied throughout all the stages. In this paper, we concentrate on this silver bullet technique within the field of side-channel. First, we address the fundamental problems of why and how to use LRA. The discussion of nominal and binary nature explains its strong applicability. To sustain effective outcomes, we provide in-depth analyses about the design matrix, regarding the sample distribution of plaintext and the chosen polynomial degree. We summarize ideal conditions that totally avoid multicollinearity problem, and explore the novel evaluator-advantageous property of LRA by means of model diagnosis. Then, we trace the roots where we theoretically elaborate its connections with traditional side-channel techniques, including Correlation Power Analysis (CPA), Distance-of-Means analysis (DoM) and Partition Power Analysis (PPA), in terms of regression coefficients, regression model and coefficient of determination. Finally, we probe into the state-of-the-art combined LRA with the so-called collapse function, demonstrating its relationship with another refined technique, G-DoM. We argue that properly relaxing the definition of bit groups equally satisfies our conclusions. Experimental results are in line with the theory, confirming its correctness.