Paper Abstract and Keywords |
Presentation |
2020-03-03 11:20
Adversarial Attack against Neural Machine Translation Systems Takeshi Sakamoto, Tatsuya Mori (Waseda Univ.) ICSS2019-89 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
It has been widely known that systems empowered by neural network algorithms are vulnerable against an intrinsic attack named ``adversarial example'', which can be generated by adding small perturbations to the original inputs, aiming at fooling the systems. In this paper, we target Neural Machine Translation (NMT) and present attacks that change the meaning of sentences by adding small perturbations to the translated sentences (Adversarial text). This attack can intentionally control the nuance of meanings for documents such as contracts, products, reviews and postings to SNS by politicians or experts, which may play a vital role in making a decision.
In this work, we adopt Google translate as a widely used NMT system and apply our attack using common sentences to study the effectiveness of the attack. We demonstrate that the meaning of sentences could be changed by 55% and the success rate is higher than the existing methods that target text classification applications. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Adversarial Example / Neural Machine Translation / Homoglyph / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 437, ICSS2019-89, pp. 125-130, March 2020. |
Paper # |
ICSS2019-89 |
Date of Issue |
2020-02-24 (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) |
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ICSS2019-89 |
Conference Information |
Committee |
ICSS IPSJ-SPT |
Conference Date |
2020-03-02 - 2020-03-03 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Okinawa-Ken-Seinen-Kaikan |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Security, Trust, etc. |
Paper Information |
Registration To |
ICSS |
Conference Code |
2020-03-ICSS-SPT |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Adversarial Attack against Neural Machine Translation Systems |
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Adversarial Example |
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Neural Machine Translation |
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Homoglyph |
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1st Author's Name |
Takeshi Sakamoto |
1st Author's Affiliation |
Waseda University (Waseda Univ.) |
2nd Author's Name |
Tatsuya Mori |
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Waseda University (Waseda Univ.) |
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Speaker |
Author-1 |
Date Time |
2020-03-03 11:20:00 |
Presentation Time |
20 minutes |
Registration for |
ICSS |
Paper # |
ICSS2019-89 |
Volume (vol) |
vol.119 |
Number (no) |
no.437 |
Page |
pp.125-130 |
#Pages |
6 |
Date of Issue |
2020-02-24 (ICSS) |
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