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Paper Abstract and Keywords
Presentation 2021-10-19 10:25
A Deep-Learning Based Single-Trace Side-Channel Attack on Tamper-Resistant CRT-RSA Software
Kotaro Saito, Akira Ito, Rei Ueno, Naofumi Homma (Tohoku Univ.) HWS2021-42 ICD2021-16
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes a deep-learning based single-trace side-channel attack on CRT-RSA software implementation secure against simple power analysis (SPA).We focus on a CRT-RSA implementation with an open-source software library named Gnu MP, which employs the fixed window (FW) exponentiation with a hiding countermeasure based on a dummy load for the sake of SPA resistance. The FW exponentiation is known as the fastest, constant-time, and SPA-resistant modular exponentiation algorithm. In addition, dummy load in selecting a multiplicand is utilized to mitigate more sophisticated power analysis/cache attacks. We propose a novel single-trace power analysis attack on the basis of deep learning to estimate the secret exponents from FW exponentiation exploiting dummy load with a convincing accuracy. Furthermore, we extend the partial key exposure attack on CRT-RSA such that it can exploit the feature of key exposure estimated by the above analysis. We experimentally demonstrate that secret keys of the CRT-RSA can be easily recovered even when the estimated exponents contain some errors.
Keyword (in Japanese) (See Japanese page) 
(in English) Side-Channel Attack / Deep-Learning / CRT-RSA / Partial Key Exposure Attack / Gnu MP / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 206, HWS2021-42, pp. 7-12, Oct. 2021.
Paper # HWS2021-42 
Date of Issue 2021-10-12 (HWS, ICD) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF HWS2021-42 ICD2021-16

Conference Information
Committee HWS ICD  
Conference Date 2021-10-19 - 2021-10-19 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Hardware Security, etc. 
Paper Information
Registration To HWS 
Conference Code 2021-10-HWS-ICD 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Deep-Learning Based Single-Trace Side-Channel Attack on Tamper-Resistant CRT-RSA Software 
Sub Title (in English)  
Keyword(1) Side-Channel Attack  
Keyword(2) Deep-Learning  
Keyword(3) CRT-RSA  
Keyword(4) Partial Key Exposure Attack  
Keyword(5) Gnu MP  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Kotaro Saito  
1st Author's Affiliation Tohoku University (Tohoku Univ.)
2nd Author's Name Akira Ito  
2nd Author's Affiliation Tohoku University (Tohoku Univ.)
3rd Author's Name Rei Ueno  
3rd Author's Affiliation Tohoku University (Tohoku Univ.)
4th Author's Name Naofumi Homma  
4th Author's Affiliation Tohoku University (Tohoku Univ.)
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Speaker Author-1 
Date Time 2021-10-19 10:25:00 
Presentation Time 25 minutes 
Registration for HWS 
Paper # HWS2021-42, ICD2021-16 
Volume (vol) vol.121 
Number (no) no.206(HWS), no.207(ICD) 
Page pp.7-12 
#Pages 6 
Date of Issue 2021-10-12 (HWS, ICD) 

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