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- Title
基于小波变换去噪的相关功耗分析 攻击研究与实现.
- Authors
段晓毅; 陈 东; 高献伟; 范晓红; 靳济方
- Abstract
In order to improve the efficiency of power analysis attack and reduce the influence of noise, this paper studied the influence of wavelet transform denoising on power attack and the correlation coefficient between correlation power analysis and attack effect. For the purpose of denoising the power consumption curve variable, this paper used wavelet method and the wavelet modulus maximum method. The method included the Kalman filter method, the wavelet modulus maximum method and the translation invariant wavelet method . Then the denoised original data were respectively subjected to CPA. Simulation experiments show that compared with the original data, the improved CPA correlation coefficient using the translation invariant wavelet method is 165% higher than using original CPA, 31.4% higher than the Kalman filter method, 26.4% higher than the wavelet modulus maximum method. Also, the power curve required for successful attack is reduced by 92% . The experimental results show that the improved power analysis using the translation invariant wavelet method has the best effect.
- Subjects
STATISTICAL correlation; WAVELET transforms; TRANSLATIONS; WAVELETS (Mathematics); NOISE; CURVES
- Publication
Application Research of Computers / Jisuanji Yingyong Yanjiu, 2020, Vol 37, Issue 4, p1119
- ISSN
1001-3695
- Publication type
Article
- DOI
10.19734/j.issn.1001-3695.2018.09.0757