基于巴特沃斯滤波算法的侧信道分析

Side-channel Analysis based on Butterworth Filtering Algorithm

基于巴特沃斯滤波算法在现场可编程逻辑门阵列(FPGA)侧信道攻击中的使用,主要利用巴特沃斯滤波算法对功耗曲线进行预处理,然后用神经网络模型代替传统模板攻击的统计模型对功耗曲线进行侧信道攻击.该算法对模板攻击,随机方法,深层感知器以及深层卷积神经网络的功耗曲线预处理具有普适性,在实验部分针对DPA CONTEST V2数据进行了4种侧信道方法的分析,实验数据表明该方法提高了可攻击的信噪比,同时提高了侧信道攻击的成功率.

This paper introduced Butterworth filtering algorithm in field programmable logic gate aiTay(FPGA)side channel attack.The power curve was preprocessed by Butterworth filtering algorithm,and the power curve was cittacked by side channel using neural network model instead of traditional template model.This algorithm is universal for the power curve pretreatment of template attack,random method,deep perceptron and deep convolutional neural network,based on the experimental section in view of the DPA CONTEST2 data which were analyzed in four methods of side channel,the experimental data showed that the method increases the signal-to-noise ratio(SNR)attacked available,and improves the success rate of side channel attack.