基于EMD与奇异值差分谱的侧信道信号特征提取  

Feature extraction of side channel signal based on EMD and difference spectrum of singular value

作　　者：姚艳丽[1] 吴震[1] 饶金涛[1] 王敏[1] 杜之波[1] YAO Yan-li WU Zhen RAO Jin-tao WANG Min DU Zhi-bo(College of Information Security Engineering, Chengdu University of Information Technology, Chengdu 610225, China)

机构地区：[1]成都信息工程大学信息安全工程学院,四川成都610225

出　　处：《网络与信息安全学报》2016年第7期69-75,共7页Chinese Journal of Network and Information Security

基　　金：国家重大科技专项基金资助项目(No.2014ZX01032401-001);国家高技术研究发展计划("863"计划)基金资助项目(No.2012AA01A403);"十二五"国家密码发展基金资助项目(No.MMJJ201101022);四川省科技支撑计划基金资助项目(No.2014GZ0148);四川省教育厅重点科研基金资助项目(No.13ZA0091);成都信息工程大学科研基金资助项目(No.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(No.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。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 similar 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 reconstructed 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.

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 

分 类 号：TP309[自动化与计算机技术—计算机系统结构] TN911[自动化与计算机技术—计算机科学与技术]