Cryptology ePrint Archive: Report 2019/1487

SNR-Centric Power Trace Extractors for Side-Channel Attacks

Changhai Ou and Degang Sun and Siew-Kei Lam and Xinping Zhou and Kexin Qiao and Qu Wang

Abstract: The existing power trace extractors consider the case that the number of power traces owned by the attacker is sufficient to guarantee his successful attacks, and the goal of power trace extraction is to lower the complexity rather than increase the success rates. Although having strict theoretical proofs, they are too simple and leakage characteristics of POIs have not been thoroughly analyzed. They only maximize the variance of data-dependent power consumption component and ignore the noise component, which results in very limited SNR to improve and seriously affects the performance of extractors. In this paper, we provide a rigorous theoretical analysis of SNR of power traces, and propose a novel SNR-centric extractor, named Shortest Distance First (SDF), to extract power traces with smallest the estimated noise by taking advantage of known plaintexts. In addition, to maximize the variance of the exploitable component while minimizing the noise, we refer to the SNR estimation model and propose another novel extractor named Maximizing Estimated SNR First (MESF). Finally, we further propose an advanced extractor called Mean optimized MESF (MMESF) that exploits the mean power consumption of each plaintext byte value to more accurately and reasonably estimate the data-dependent power consumption of the corresponding samples. Experiments on both simulated power traces and measurements from an ATmega328p micro-controller demonstrate the superiority of our new extractors.

Category / Keywords: implementation / shortest distance first, SDF, MESF, signal-to-noise ratio, SNR, power trace extractor, side-channel attack.

Date: received 26 Dec 2019

Contact author: chou at ntu edu sg

Available format(s): PDF | BibTeX Citation

Version: 20191230:193238 (All versions of this report)

Short URL: ia.cr/2019/1487


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