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Paper Abstract and Keywords
Presentation 2023-02-22 10:15
Generation Method of Targeted Adversarial Examples using Gradient Information for the Target Class of the Image
Ryo Kumagai, Shu Takemoto, Yusuke Nozaki, Masaya Yoshikawa (Meijo Univ.) ITS2022-61 IE2022-78
Abstract (in Japanese) (See Japanese page) 
(in English) With the advancement of AI technology, the vulnerability of AI system is pointed out. The adversarial examples (AE), which causes wrong decisions by AI, is one of the terrible attacks for AI. Thus thorough investigation for AEs is mandatory required to use AI safely. This paper propose the generating method for adversarial examples which is using the gradient information for the target class of the input image. Experiments prove the proposed method can generate a targeted AE that misclassifies into an arbitrary class with high probability.
Keyword (in Japanese) (See Japanese page) 
(in English) deep neural networks / security / adversarial examples / / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 385, IE2022-78, pp. 107-111, Feb. 2023.
Paper # IE2022-78 
Date of Issue 2023-02-14 (ITS, IE) 
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 ITS2022-61 IE2022-78

Conference Information
Committee IE ITS ITE-MMS ITE-ME ITE-AIT  
Conference Date 2023-02-21 - 2023-02-22 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To IE 
Conference Code 2023-02-IE-ITS-MMS-ME-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Generation Method of Targeted Adversarial Examples using Gradient Information for the Target Class of the Image 
Sub Title (in English)  
Keyword(1) deep neural networks  
Keyword(2) security  
Keyword(3) adversarial examples  
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1st Author's Name Ryo Kumagai  
1st Author's Affiliation Meijo University (Meijo Univ.)
2nd Author's Name Shu Takemoto  
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.)
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Speaker Author-1 
Date Time 2023-02-22 10:15:00 
Presentation Time 15 minutes 
Registration for IE 
Paper # ITS2022-61, IE2022-78 
Volume (vol) vol.122 
Number (no) no.384(ITS), no.385(IE) 
Page pp.107-111 
#Pages 5 
Date of Issue 2023-02-14 (ITS, IE) 

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