Security evaluation of cryptographic modules against profiling attacks

Yongdae Kim, Naofumi Homma, Takafumi Aoki, Heebong Choi

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

3 Citations (Scopus)

Abstract

Recently, profiling attacks have been attracting a great deal of attention because of their increasing efficiency. Further investigations are required to determine the potential threats of the profiling attacks. This paper focuses on these attacks. Using hardware and software implementations, we provide a security evaluation of three different types of profiling attacks: template attack, stochastic model attack, and multivariate regression attack. Our experimental results show that multivariate regression attack outperforms other attacks in terms of profiling efficiency and key extraction rates.

Original languageEnglish
Title of host publicationInformation Security and Cryptology, ICISC 2012 - 15th International Conference, Revised Selected Papers
Pages383-394
Number of pages12
DOIs
Publication statusPublished - 2013 Apr 15
Event15th International Conference on Information Security and Cryptology, ICISC 2012 - Seoul, Korea, Republic of
Duration: 2012 Nov 282012 Nov 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7839 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th International Conference on Information Security and Cryptology, ICISC 2012
CountryKorea, Republic of
CitySeoul
Period12/11/2812/11/30

Keywords

  • multivariate regression analysis
  • power analysis attack
  • profiling attack
  • stochastic model attack
  • template attack

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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