Abstract
Correlation electromagnetic analysis (CEMA) is a method prevalent in side-channel analysis of cryptographic devices. Its success mostly depends on the quality of electromagnetic signals acquired from the devices. In the past, only one byte of the key was analyzed and other bytes were regarded as noise. Apparently, other bytes’ useful information was wasted, which may increase the difficulty of recovering the key. Multi-objective optimization is a good way to solve the problem of a single byte of the key. In this work, we applied multi-objective optimization to correlation electromagnetic analysis taking all bytes of the key into consideration. Combining the advantages of multi-objective optimization and genetic algorithm, we put forward a novel multi-objective electromagnetic analysis based on a genetic algorithm to take full advantage of information when recovering the key. Experiments with an Advanced Encryption Standard (AES) cryptographic algorithm on a Sakura-G board demonstrate the efficiency of our method in practice. The experimental results show that our method reduces the number of traces required in correlation electromagnetic analysis. It achieved approximately 42.72% improvement for the corresponding case compared with CEMA.
Highlights
With the development of Internet of Things (IoT) technology, ever more smart home devices are appearing in people’s lives, such as mobile phones, smart door locks, smart televisions, sensor networks and many other things
The remainder of the paper is organized as follows: in Section 2, we present related works and basic knowledge about the cryptographic algorithm, genetic algorithm and multi-objective optimization used in our experiment
The hamming distance model used in our method to estimate hypothetical electromagnetic leakage is: L = α ∙ HD(X, Y) + β = α ∙ HW(X⨁Y) + β where L is electromagnetic leakage, HW(X⨁Y) is the hamming distance between X and Y which is known as the number of flipping bits between X and Y, HW is hamming weight, α is a scalar gain and β is usually considered as noise
Summary
Shaofei Sun 1 , Hongxin Zhang 1, *, Liang Dong 1,2 , Xiaotong Cui 1 , Weijun Cheng 3 and Muhammad Saad Khan 4. Communication and Electronic Engineering Institute, Qiqihar University, Qiqihar 161006, China. Received: 25 October 2019; Accepted: 11 December 2019; Published: 15 December 2019
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