A Statistics-based Fundamental Model for Side-channel Attack Analysis.
Yunsi Fei, Aidong Adam Ding, Jian Lao, Liwei Zhang · 2014
Abstract. Side-channel attacks (SCAs) exploit leakage from the physi-cal implementation of cryptographic algorithms to recover the otherwise secret information. In the last decade, popular SCAs like differential power analysis (DPA) and correlation power analysis (CPA) have been invented and demonstrated to be realistic threats to many critical em-bedded systems. However, there is still no sound and provable theoretical model that illustrates precisely what the success of these attacks depends on and how. Based on the maximum likelihood estimation (MLE) theory, this paper proposes a general statistical model for side-channel attack analysis that takes characteristics of both the physical implementation and cryptographic algorithm into consideration. The model establishes analytical relations between the success rate of attacks and the crypto-graphic system. For power analysis attacks, the side-channel character-istic of the physical implementation is modeled as signal-to-noise ratio (SNR), which is the ratio between the single-bit unit power consumption