Perceived Information Revisited

نویسندگان

چکیده

In this study, we present new analytical metrics for evaluating the performance of side-channel attacks (SCAs) by revisiting perceived information (PI), which is defined using cross-entropy (CE). PI represents amount utilized a probability distribution that determines distinguishing rule in SCA. Our analysis partially solves an important open problem evaluation deep-learning based SCAs (DL-SCAs) relationship between neural network (NN) model (such as accuracy, loss, and recall) guessing entropy (GE)/success rate (SR) unclear. We first theoretically show conventional CE/PI non-calibrated insufficient SCA performance, it contains uncertainty terms SR. More precisely, infinite number distributions with different can achieve identical With above result, modification CE/PI, named effective (ECE/EPI), to eliminate uncertainty. The ECE/EPI be easily calculated given dataset, would suitable DL-SCA. Using ECE/EPI, accurately evaluate SR hrough validation loss training phase, measure generalization NN attack phase. then analyze discuss proposed regarding their SR, conditions successful distribution, statistic/asymptotic aspect, order key ranks Finally, validate through experimental on masked AES implementations

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ژورنال

عنوان ژورنال: IACR transactions on cryptographic hardware and embedded systems

سال: 2022

ISSN: ['2569-2925']

DOI: https://doi.org/10.46586/tches.v2022.i4.228-254