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基于EMD与奇异值差分谱的侧信道信号特征提取
引用本文:姚艳丽,吴震,饶金涛,王敏,杜之波. 基于EMD与奇异值差分谱的侧信道信号特征提取[J]. 网络与信息安全学报, 2016, 2(7): 69-75. DOI: 10.11959/j.issn.2096-109x.2016.00069
作者姓名:姚艳丽  吴震  饶金涛  王敏  杜之波
作者单位:成都信息工程大学信息安全工程学院,四川 成都 610225
基金项目:国家重大科技专项基金资助项目(2014ZX01032401-001);国家高技术研究发展计划(“863”计划)基金资助项目(2012AA01A403);“十二五”国家密码发展基金资助项目(MMJJ201101022);四川省科技支撑计划基金资助项目(2014GZ0148);四川省教育厅重点科研基金资助项目(13ZA0091);成都信息工程大学科研基金资助项目(CRF201301);成都信息工程大学中青年学术带头人科研基金资助项目(J201610)
摘    要:为了从强烈的背景噪声中提取侧信道信号的特征信息,提出了一种基于经验模式分解(EMD)与奇异值差分谱相结合的信号特征提取方法。该方法首先对原始侧信道信号进行EMD分解,计算各个特征模态函数(IMF)与原始信号的相关系数,找到最大相似特征分量;再对该分量进行奇异值分解求出对应的奇异值差分谱;最后根据差分谱进行重构和消噪,进一步提取分量的特征信息。实验结果表明,该方法可以有效应用于侧信道信号的特征提取,成功提高信号的信噪比和攻击成功率。

关 键 词:侧信道信号  经验模式分解  奇异值差分谱  特征提取  攻击成功率  

Feature extraction of side channel signal based on EMD and difference spectrum of singular value
Yan-li YAO,Zhen WU,Jin-tao RAO,Min WANG,Zhi-bo DU. Feature extraction of side channel signal based on EMD and difference spectrum of singular value[J]. Chinese Journal of Network and Information Security, 2016, 2(7): 69-75. DOI: 10.11959/j.issn.2096-109x.2016.00069
Authors:Yan-li YAO  Zhen WU  Jin-tao RAO  Min WANG  Zhi-bo DU
Affiliation:College of Information Security Engineering,Chengdu University of Information Technology,Chengdu 610225,China
Abstract:In order to extract feature information of side channel signal from the strong noise,the approach of signal feature extraction was proposed on account of empirical mode decomposition (EMD) and difference spectrum of singular value.Firstly,using EMD to decompose the original side channel signal,the correlation coefficient between all the intrinsic mode functions (IMF) and the original signal were calculated to find the component of biggest simi-lar characteristic.Then,to make a singular value decomposition of IMF component and corresponding difference spectrum of singular values was obtained.Finally,according to the difference spectrum,the filtered and recon-structed signal of IMF component was obtained,and the feature information of component was further extracted.The actual examples show that the method can extract characteristic information of side channel signal validly and improve the SNR and success rate of attack of signal successfully.
Keywords:side channel singnal  empirical mode decomposition  difference spectrum of singular value  feature ex-traction  attack success rate  
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