Paper Abstract and Keywords |
Presentation |
2022-06-16 14:40
Adversarial Robustness of Secret Key-Based Defenses against AutoAttack Miki Tanaka, April Pyone MaungMaung (Tokyo Metro Univ.), Isao Echizen (NII), Hitoshi Kiya (Tokyo Metro Univ.) CAS2022-7 VLD2022-7 SIP2022-38 MSS2022-7 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Deep neural network (DNN) models are well-known to easily misclassify prediction results by using input images with small perturbations, called adversarial examples, so investigating countermeasures for adversarial examples is an urgent issue. In this paper, the secret key-based defense that we proposed is evaluated in terms of robustness against adversarial examples in accordance with a benchmark attack method, called AutoAttack. In addition, we propose a detection method of adversarial examples to be combined with the secret key-based defense. In an experiment, the secret key-based classification model is confirmed that it is not robust enough against a black box attack, and the combined use of the key-based defense and the proposed detector outperforms the latest benchmark. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Adversarial example / Machine learning / Deep learning / Adversarial detection / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 77, SIP2022-38, pp. 34-39, June 2022. |
Paper # |
SIP2022-38 |
Date of Issue |
2022-06-09 (CAS, VLD, SIP, MSS) |
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) |
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CAS2022-7 VLD2022-7 SIP2022-38 MSS2022-7 |
Conference Information |
Committee |
CAS SIP VLD MSS |
Conference Date |
2022-06-16 - 2022-06-17 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Hachinohe Institute of Technology |
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(See Japanese page) |
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Paper Information |
Registration To |
SIP |
Conference Code |
2022-06-CAS-SIP-VLD-MSS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Adversarial Robustness of Secret Key-Based Defenses against AutoAttack |
Sub Title (in English) |
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Adversarial example |
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Machine learning |
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Deep learning |
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Adversarial detection |
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1st Author's Name |
Miki Tanaka |
1st Author's Affiliation |
Tokyo Metropolitan University (Tokyo Metro Univ.) |
2nd Author's Name |
April Pyone MaungMaung |
2nd Author's Affiliation |
Tokyo Metropolitan University (Tokyo Metro Univ.) |
3rd Author's Name |
Isao Echizen |
3rd Author's Affiliation |
National Institute of Informatics (NII) |
4th Author's Name |
Hitoshi Kiya |
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Tokyo Metropolitan University (Tokyo Metro Univ.) |
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Speaker |
Author-1 |
Date Time |
2022-06-16 14:40:00 |
Presentation Time |
25 minutes |
Registration for |
SIP |
Paper # |
CAS2022-7, VLD2022-7, SIP2022-38, MSS2022-7 |
Volume (vol) |
vol.122 |
Number (no) |
no.75(CAS), no.76(VLD), no.77(SIP), no.78(MSS) |
Page |
pp.34-39 |
#Pages |
6 |
Date of Issue |
2022-06-09 (CAS, VLD, SIP, MSS) |
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