一种基于奇异值分解的功耗轨迹筛选方法

A Method Based on Singular Value Decomposition for Enhancement of Differential Power Analysis

功耗分析攻击是侧信道分析中针对密码设备最有效的分析手段之一,它利用密码设备消耗的功耗来分析密码设备的敏感信息.差分功耗分析是最早提出的功耗分析方法,也是目前最基本的分析方法之一.但是在实际使用差分功耗分析过程中,由于功耗轨迹存在噪声等因素,往往使得花了较多的功耗轨迹,差分功耗分析的效果一般,难以恢复出正确密钥.针对这个问题,本文提出了一种基于奇异值分解的选择功耗轨迹方法,这种方法可以选择一些质量好的功耗轨迹用于差分功耗分析,提高差分功耗分析的攻击效率.本文的实验验证了该方法的有效性,在同等分析条件下,对于我们自己采集的功耗数据,使用该方法情况下仅需124条功耗轨迹就可以达到80%的成功率,而普通差分功耗分析需要490条;对于DPA Contest 2008/2009提供的数据,使用该方法仅需53条功耗轨迹可以达到80%的成功率,而普通差分功耗分析需要195条.两个不同的实验对象都说明了该方法的有效性.

Power analysis is one of the most effective techniques in side channel analysis. This technique utilizes the power consumption that are relative to the intermediate state of cryptographic algorithm to recover the secret information in the cryptographic devices. Differential power analysis is the first method of power analysis and it is one of the most fundamental analysis techniques. However,in practical scenario,the efficiency of differential power analysis is largely affected by the noise of power traces. Consequently,this leads to the lowefficiency of differential power analysis and it is hard to recover the secret key. To address this issue,a newmethod that is based on singular value decomposition to select power traces is proposed. The power traces of high quality can be selected when this method is applied to improve the efficiency of differential power analysis. The experiments verify the validity of the method. Further,the experimental results showthat our method is much better compared with the existing method. Using the method of this paper only 124 power traces is needed to achieve the success rate of 80%,while the normal differential power analysis needs 490 power traces. In addition,when analyzing the data of DPA Contest V1,using the method of this paper only 53 power traces is needed to achieve the success rate of 80%,while the normal differential power analysis needs 195 power traces. Two experiments on different subjects verify the effectiveness of our method.