Presentation 2014-07-04
Quantitative Evaluation of the Key Information That is Learned through Timing Attack : The Contribution of Bucketing Technique for RSA Cryptosystem
Yasuyuki KOBAYASHI, Yuichi KAJI, Hiroyuki SEKI, Minoru ITO,
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Abstract(in English) Timing attacks are regarded as serious threats to many practical cryptographic algorithms, but it is difficult to estimate the risk of the attack because we cannot predict the ability and the behavior of attackers. To tackle this issue, Kopf et al. focus on the mutual information between a secret key and timing observations that an attacker acquires. The discussion of this approach gives a certain upper-bound on the risk of timing attacks. Kopf et al. adopted this approach to evaluate the contribution of a bucketing technique that was proposed by themselves, but the mathematical discussion therein needs more improvement. The purpose of this study is to refine the discussion of Kopf. We assume that element distribution of the running time polynomial distribution, and give the upper-bound of the mutual information that is tighter than the conventional method. Furthermore, Simulation results suggest that proposed method give more precise understanding of the contribution of the bucketing technique.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Timing Attack / Side-channel Attack / Bucketing of Running Time / Information Theory / Quantitative Information Flow Analysis / Multinomial Distribution
Paper # ISEC2014-35,SITE2014-30,ICSS2014-39,EMM2014-35
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Committee SITE
Conference Date 2014/6/26(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Quantitative Evaluation of the Key Information That is Learned through Timing Attack : The Contribution of Bucketing Technique for RSA Cryptosystem
Sub Title (in English)
Keyword(1) Timing Attack
Keyword(2) Side-channel Attack
Keyword(3) Bucketing of Running Time
Keyword(4) Information Theory
Keyword(5) Quantitative Information Flow Analysis
Keyword(6) Multinomial Distribution
1st Author's Name Yasuyuki KOBAYASHI
1st Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology()
2nd Author's Name Yuichi KAJI
2nd Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology
3rd Author's Name Hiroyuki SEKI
3rd Author's Affiliation Graduate School of Information Science, Nagoya University
4th Author's Name Minoru ITO
4th Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology
Date 2014-07-04
Paper # ISEC2014-35,SITE2014-30,ICSS2014-39,EMM2014-35
Volume (vol) vol.114
Number (no) 116
Page pp.pp.-
#Pages 6
Date of Issue