An Electromagnetic Approach to Smart Card Instruction Identification using Machine Learning Techniques

被引：0

作者：

Tsague, Hippolyte Djonon ^{[1
]}

Twala, Bheki ^{[2
]}

机构：

[1] SIR, MDS, Smart Token Res Grp, Pretoria, South Africa

[2] Univ Johannesburg, Fac Engn, Inst Intelligent Syst, Dept Elect & Elect Engn Sci, Johannesburg, South Africa

来源：

2017 IEEE SMARTWORLD, UBIQUITOUS INTELLIGENCE & COMPUTING, ADVANCED & TRUSTED COMPUTED, SCALABLE COMPUTING & COMMUNICATIONS, CLOUD & BIG DATA COMPUTING, INTERNET OF PEOPLE AND SMART CITY INNOVATION (SMARTWORLD/SCALCOM/UIC/ATC/CBDCOM/IOP/SCI) | 2017年

关键词：

Side Channel Leakage; Electromagnetic Templates; Principal Components Analysis; Linear Discriminant Analysis; Multivariate Gaussian Distribution; k-Nearest Neighbours Algorithm; Reverse Engineering; POWER;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Since the first publication, side channel leakage has been widely used for the purposes of extracting secret information, such as cryptographic keys, from embedded devices. However, in a few instances it has been utilized for extracting other information about the internal state of a computing device. In this paper, we show how to create a robust instruction-level side channel leakage profile of an embedded processor. Using the electromagnetic profile we show how to extract executed instructions from a smart card's leakage with good accuracy. In addition, we provide a comparison between several performance and recognition enhancement tools.

引用

页数：8

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