A Robust Machine Learning Approach to Microprocessor Instructions Identification

被引：0
作者：
Tsague, Hippolyte Djonon [1 ]
Twala, Bheki [2 ]
机构：
[1] CSIR, Smart Token Res Grp, MDS, Pretoria, South Africa
[2] Univ Johannesburg, Fac Engn, Inst Intelligent Syst, Dept Elect & Elect Engn Sci, Johannesburg, South Africa
来源：
ADVANCES IN SOFT COMPUTING, MICAI 2016, PT II | 2017年 / 10062卷
关键词：
Side channel leakage; Templates; Principal Components Analysis; Linear Discriminant Analysis; Multivariate gaussian distribution; k-Nearest Neighbours Algorithm; Reverse engineering; POWER;
D O I：
10.1007/978-3-319-62428-0_21
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
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 utilised 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 profile we show how to extract executed instructions from the device's leakage with good accuracy. In addition, we provide a comparison between several performance and recognition enhancement tools.
引用
收藏
页码：248 / 258
页数：11
相关论文
共 14 条
  • [1] [Anonymous], 2001, LNCS, DOI DOI 10.1007/3-540-45418-7
  • [2] Bishop C., 2006, Pattern recognition and machine learning, P423
  • [3] Clavier Christophe, 2013, Progress in Cryptology - INDOCRYPT 2013. 14th International Conference on Cryptology in India. Proceedings: LNCS 8250, P116, DOI 10.1007/978-3-319-03515-4_8
  • [4] Clavier C., 2004, Side channel analysis for reverse engineering (scare)-an improved attack against a secret a3/a8 gsm algorithm
  • [5] Eisenbarth T, 2008, LECT NOTES COMPUT SC, V5157, P203, DOI 10.1007/978-3-540-85174-5_12
  • [6] Goldack M., 2008, THESIS
  • [7] Mousa A., 2006, Int. J. Comput. Sci. Appl, V3, P44
  • [8] Msgna Mehari, 2014, Information Security Practice and Experience. 10th International Conference, ISPEC 2014. Proceedings: LNCS 8434, P129, DOI 10.1007/978-3-319-06320-1_11
  • [9] Nasrabadi N. M, 2007, J ELECTRON IMAGING, V16, P33
  • [10] Novak R, 2003, LECT NOTES COMPUT SC, V2846, P307
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