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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 |
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| 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 |
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| 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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