Information: Join today and make your research activities more affordable! Technical workshop participation fees and annual registration fees are available at member rates.
Notice: [Important] Announcement of Changes to Registration Fee Payment and Manuscript Upload Procedures for IEICE Technical Meetings
IEICE Technical Committee Submission System
Conference Paper's Information		 Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2022-07-28 16:30
Deep Learning Power Analysis Against Protected PRINCE
Shu Takemoto, Yoshiya Ikezaki, Yusuke Nozaki, Masaya Yoshikawa (Meijo Univ.) SS2022-4 KBSE2022-14
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, with the development of deep learning, AI has been incorporated in the field of cyber security. On the other hand, AI has been reported to be used not only to improve security but also for cyber-attacks. One of the cyber attacks is a malicious attack called a power analysis attack, which analyzes the secret information of a cryptographic device. Recently, deep learning power analysis attack has been proposed as an efficient method using deep learning. Therefore, it is important to evaluate deep learning power analysis attacks on cryptographic devices. In particular, cryptographic algorithms that can be implemented in a small area are suitable for IoT devices with implementation constraints. Several such cryptographic algorithms have been proposed as lightweight block cipher. Therefore, this study demonstrates a deep learning power analysis attack on PRINCE as a representative lightweight block cipher. Also, this study implements PRINCE with masking countermeasures on an evaluation device and evaluates the learning rate of the Hamming distance by deep learning.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep Learning / Hardware Security / Lightweight Block Cipher / Side-Channel Attack / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 139, KBSE2022-14, pp. 19-24, July 2022.
Paper # KBSE2022-14 
Date of Issue 2022-07-21 (SS, KBSE) 
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 SS2022-4 KBSE2022-14

Conference Information
Committee SS IPSJ-SE KBSE  
Conference Date 2022-07-28 - 2022-07-30 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido-Jichiro-Kaikan (Sapporo) 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To KBSE 
Conference Code 2022-07-SS-SE-KBSE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Deep Learning Power Analysis Against Protected PRINCE 
Sub Title (in English)  
Keyword(1) Deep Learning  
Keyword(2) Hardware Security  
Keyword(3) Lightweight Block Cipher  
Keyword(4) Side-Channel Attack  
Keyword(5)  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Shu Takemoto  
1st Author's Affiliation Meijo University (Meijo Univ.)
2nd Author's Name Yoshiya Ikezaki  
2nd Author's Affiliation Meijo University (Meijo Univ.)
3rd Author's Name Yusuke Nozaki  
3rd Author's Affiliation Meijo University (Meijo Univ.)
4th Author's Name Masaya Yoshikawa  
4th Author's Affiliation Meijo University (Meijo Univ.)
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
21st Author's Name  
21st Author's Affiliation ()
22nd Author's Name  
22nd Author's Affiliation ()
23rd Author's Name  
23rd Author's Affiliation ()
24th Author's Name  
24th Author's Affiliation ()
25th Author's Name  
25th Author's Affiliation ()
26th Author's Name / /
26th Author's Affiliation ()
()
27th Author's Name / /
27th Author's Affiliation ()
()
28th Author's Name / /
28th Author's Affiliation ()
()
29th Author's Name / /
29th Author's Affiliation ()
()
30th Author's Name / /
30th Author's Affiliation ()
()
31st Author's Name / /
31st Author's Affiliation ()
()
32nd Author's Name / /
32nd Author's Affiliation ()
()
33rd Author's Name / /
33rd Author's Affiliation ()
()
34th Author's Name / /
34th Author's Affiliation ()
()
35th Author's Name / /
35th Author's Affiliation ()
()
36th Author's Name / /
36th Author's Affiliation ()
()
Speaker Author-1 
Date Time 2022-07-28 16:30:00 
Presentation Time 25 minutes 
Registration for KBSE 
Paper # SS2022-4, KBSE2022-14 
Volume (vol) vol.122 
Number (no) no.138(SS), no.139(KBSE) 
Page pp.19-24 
#Pages 6 
Date of Issue 2022-07-21 (SS, KBSE) 

[Return to Top Page]

[Return to IEICE Web Page]
The Institute of Electronics, Information and Communication Engineers (IEICE), Japan