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Paper Abstract and Keywords
Presentation 2022-06-24 10:25
Application of Adversarial Examples to Physical ECG Signals
Taiga Ono (Waseda Univ.), Takeshi Sugawara (UEC), Jun Sakuma (Tsukuba Univ./RIKEN), Tatsuya Mori (Waseda Univ./RIKEN/NICT) IA2022-11 ICSS2022-11
Abstract (in Japanese) (See Japanese page) 
(in English) This work aims to assess the reality and feasibility of applying adversarial examples to attack cardiac diagnosis systems powered by machine learning algorithms. To this end, we introduce "adversarial beats", which are adversarial perturbations tailored specifically against classification systems designed to diagnose electrocardiograms (ECGs). We formulate an algorithm to generate adversarial beats, and evaluate their feasibility in a physical environment by designing a hardware attack. To the best of our knowledge, our work is the first in evaluating the proficiency of adversarial examples for ECGs in a physical setup. Our real-world experiments demonstrate that against an automated ECG diagnosis setup, we can leverage our proposed method to fake the presence of potential signs of cardiomyopathy with approximately 42.1% chance of success. We conclude that our proposed method can be leveraged by attackers to influence clinical decisions, which could be applied to fraudulent clinical transactions.
Keyword (in Japanese) (See Japanese page) 
(in English) DNN / Adversarial Examples / Hardware / / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 86, ICSS2022-11, pp. 61-66, June 2022.
Paper # ICSS2022-11 
Date of Issue 2022-06-16 (IA, ICSS) 
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 IA2022-11 ICSS2022-11

Conference Information
Committee IA ICSS  
Conference Date 2022-06-23 - 2022-06-24 
Place (in Japanese) (See Japanese page) 
Place (in English) Univ. of Nagasaki 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Internet Security, etc. 
Paper Information
Registration To ICSS 
Conference Code 2022-06-IA-ICSS 
Language English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Application of Adversarial Examples to Physical ECG Signals 
Sub Title (in English)  
Keyword(1) DNN  
Keyword(2) Adversarial Examples  
Keyword(3) Hardware  
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1st Author's Name Taiga Ono  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Takeshi Sugawara  
2nd Author's Affiliation The University of Electro-Communications (UEC)
3rd Author's Name Jun Sakuma  
3rd Author's Affiliation University of Tsukuba/RIKEN (Tsukuba Univ./RIKEN)
4th Author's Name Tatsuya Mori  
4th Author's Affiliation Waseda University/RIKEN/National Institute of Information and Communications Technology (Waseda Univ./RIKEN/NICT)
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Speaker Author-1 
Date Time 2022-06-24 10:25:00 
Presentation Time 25 minutes 
Registration for ICSS 
Paper # IA2022-11, ICSS2022-11 
Volume (vol) vol.122 
Number (no) no.85(IA), no.86(ICSS) 
Page pp.61-66 
#Pages 6 
Date of Issue 2022-06-16 (IA, ICSS) 

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