Power consumption attack efficient screening method based on genetic algorithm

Abstract

The invention discloses a power consumption attack efficient screening method based on a genetic algorithm. The method comprises: collecting power consumption; determining parameters and a fitness function; initializing a population; calculating individual fitness; calculating byte fitness; selecting an excellent individual stage; a crossing stage; and a variation stage. According to the method, the power consumption attack technology in the side channel analysis technology is combined, and the traditional power consumption attack is combined with the improved genetic algorithm, so that the calculation complexity of the traditional power consumption attack is reduced, and the attack efficiency and success rate are improved; and meanwhile, the problems of individual degradation and low evolution speed in a traditional genetic algorithm and power consumption attack combined method are solved.

Description

technical field [0001] The invention belongs to the field of side channel analysis, and in particular relates to a genetic algorithm-based efficient screening method for power consumption attacks, which can improve attack efficiency and reduce resource complexity such as calculation. Background technique [0002] In side-channel attacks, side-channel attacks based on power consumption are the most common attack methods. As the name implies, power consumption attacks are based on power consumption information generated by cryptographic chips, cryptographic devices, or cryptographic modules during cryptographic algorithms. A side-channel attack method of the attack. Similarly, power consumption attacks can also be divided into many different analysis methods: in 2002, the simple power attack (Simple Power Attack, SPA) proposed by Joong et al., the differential power attack (Differential Power Attack, SPA) proposed by Kocher et al. Attack, DPA), Correlation Power Attack (CPA) ...

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Problems solved by technology

But so far, there are still deficiencies in these methods that combine genetic algorithms and power consumption attacks, as well as in the subsequent improved methods, so this project will conduct research on these deficiencies and overcome these deficiencies. achieve better results

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