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.
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收藏
页数：8
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