Side channel analysis of an elliptic curve crypto-system based on multi-class classification

Ehsan Saeedi, Md Selim Hossain, Yinan Kong

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Abstract

Cryptosystems, even after recent algorithmic improvements, can be vulnerable to side channel attacks (SCA). In this paper, we investigated one of the powerful class of SCA based on machine learning techniques in the forms of Principal Component Analysis (PCA) and multi-class classification. For this purpose, support vector machine (SVM) is investigated as a robust and efficient multi-class classifier along with a proper kernel function and its appropriate parameters. Our experiment performed on data leakage of FPGA implementation of elliptic curve cryptography (ECC), and the results, validated by cross validation approach, compare the efficiency of different kernel functions and the influence of function parameters.

Original languageEnglish
Title of host publication6th International Conference on Computing, Communications and Networking Technologies, ICCCNT 2015
Place of PublicationPiscataway, USA
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-7
Number of pages7
ISBN (Electronic)9781479979844
DOIs
Publication statusPublished - 2015
Event6th International Conference on Computing, Communications and Networking Technologies, ICCCNT 2015 - Denton, United States
Duration: 13 Jul 201515 Jul 2015

Other

Other6th International Conference on Computing, Communications and Networking Technologies, ICCCNT 2015
CountryUnited States
CityDenton
Period13/07/1515/07/15

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