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Paper Abstract and Keywords
Presentation 2024-01-17 10:55
Detecting Adversarial Examples using Filtering Operation Based on JPEG-Compression-Derived Distortion
Kenta Tsunomori (Okayama Univ.), Minoru Kuribayashi (Tohoku Univ.), Nobuo Funabiki (Okayama Univ.) EMM2023-87
Abstract (in Japanese) (See Japanese page) 
(in English) Image classifiers based on convolutional neural networks are caused misclassification by adversarial perturbations. In this paper, we propose a method to use the difference images before and after applying the denoising filter to the input images for training the adversarial examples detection system. The proposed method employs the distortion signals modulated by the difference information of the images before and after JPEG compression as the denoising filter. Results of this research. The proposed method shows the adversarial examples detection accuracy of more than 98%.
Keyword (in Japanese) (See Japanese page) 
(in English) adversarial examples / denoising filter / Fine tuning / JPEG compression / Scaling / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 332, EMM2023-87, pp. 38-43, Jan. 2024.
Paper # EMM2023-87 
Date of Issue 2024-01-09 (EMM) 
ISSN Online edition: ISSN 2432-6380
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 EMM2023-87

Conference Information
Committee EMM  
Conference Date 2024-01-16 - 2024-01-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Sense of Presence, Universal Media, Digital Entertainment, etc. 
Paper Information
Registration To EMM 
Conference Code 2024-01-EMM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Detecting Adversarial Examples using Filtering Operation Based on JPEG-Compression-Derived Distortion 
Sub Title (in English)  
Keyword(1) adversarial examples  
Keyword(2) denoising filter  
Keyword(3) Fine tuning  
Keyword(4) JPEG compression  
Keyword(5) Scaling  
1st Author's Name Kenta Tsunomori  
1st Author's Affiliation Okayama University (Okayama Univ.)
2nd Author's Name Minoru Kuribayashi  
2nd Author's Affiliation Tohoku University (Tohoku Univ.)
3rd Author's Name Nobuo Funabiki  
3rd Author's Affiliation Okayama University (Okayama Univ.)
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Speaker Author-1 
Date Time 2024-01-17 10:55:00 
Presentation Time 25 minutes 
Registration for EMM 
Paper # EMM2023-87 
Volume (vol) vol.123 
Number (no) no.332 
Page pp.38-43 
Date of Issue 2024-01-09 (EMM) 

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