Paper 2020/1164

Template Attacks Based on the Multivariate Joint Distribution

Min Yang, Qingshu Meng, An Wang, and Xin Liu

Abstract

For template attacks, it is ideal if templates can be built for each (data,key) pair. However, it requires a lot of power traces and computation. In this paper, firstly, the properties of the UMJD(unisource multivariate joint distribution) are studied, and then a template attack based on the UMJD is presented. For power traces with much noise, the experiments show that its attack effect is much better than that of the CPA(correlation power analysis) based template attacks and that of the SOST(sum of square wise pair t-differences) based template attacks. Secondly, the problem to build a template for each (data,key) pair can be reduced to build templates for an MMJD (multisource multivariate joint distribution). An MMJD can be divided into several UMJDs. Based on the analysis, we give a template attack that does not require large amounts of computations, and neither a large number of power traces for profiling, but with its attack effect equivalent to that of the template attack which aims to build a template for each (data,key) pair. Third, from the process of the UMJD based template attacks, using the POI (points of interest) of all variables together as the POI of the template attack is an extension to the existing conclusion on the optimal number of POI. Lastly, the UMJD can also be applied in the SOST method to obtain better quality of POI.