Security evaluation of cryptographic modules against profiling attacks

  • Authors:
  • Yongdae Kim;Naofumi Homma;Takafumi Aoki;Heebong Choi

  • Affiliations:
  • The Attached Institute of Electronics and Telecommunications Research Institute, Korea;Graduate School of Information Sciences, Tohoku University, Japan;Graduate School of Information Sciences, Tohoku University, Japan;The Attached Institute of Electronics and Telecommunications Research Institute, Korea

  • Venue:
  • ICISC'12 Proceedings of the 15th international conference on Information Security and Cryptology
  • Year:
  • 2012

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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.