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| Presentation | 2019-11-13 14:20 Issue on Adversarial Malware Sample Generation using Reinforcement Learning against Machine Learning Based Malware Detection System Seiya Takagi, Hirokazu Hasegawa, Yukiko Yamaguchi, Hajime Shimada (Nagoya Univ.)  ICSS2019-62 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In recent years, security researchers have applied machine learning techniques to malware detection researches to improve detection rate of unknown malware that appears continuously. Furthermore, machine learning is already reflected to commercial counter malware solutions and some of them appeals effectiveness for unknown malware. However, some researchers also proposed various method to attack the machine learning based malware detection. So, to keep effectiveness of machine learning based malware detection,we have to promote researches to realize countermeasure with finding probable attack methods beforehand. In this research, we tried to construct a method to generate adversarial samples which aims to decrease detection rate for a specific malware to proof probability of data poisoning attack for machine learning based malware detection. We discuss current problems with trial results. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Malware Detection / Adversarial Sample / Data Poisoning Attack / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 288, ICSS2019-62, pp. 13-18, Nov. 2019. | |
| Paper # | ICSS2019-62 | |
| Date of Issue | 2019-11-06 (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) | |
| Download PDF | ICSS2019-62 |
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| Conference Information | |
| Committee | ICSS |
| Conference Date | 2019-11-13 - 2019-11-13 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | MRT Terrace(Miyazaki) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Information Communication System Security, etc. |
| Paper Information | |
| Registration To | ICSS |
| Conference Code | 2019-11-ICSS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Issue on Adversarial Malware Sample Generation using Reinforcement Learning against Machine Learning Based Malware Detection System |
| Sub Title (in English) | |
| Keyword(1) | Malware Detection |
| Keyword(2) | Adversarial Sample |
| Keyword(3) | Data Poisoning Attack |
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| Keyword(8) | |
| 1st Author's Name | Seiya Takagi |
| 1st Author's Affiliation | Nagoya University (Nagoya Univ.) |
| 2nd Author's Name | Hirokazu Hasegawa |
| 2nd Author's Affiliation | Nagoya University (Nagoya Univ.) |
| 3rd Author's Name | Yukiko Yamaguchi |
| 3rd Author's Affiliation | Nagoya University (Nagoya Univ.) |
| 4th Author's Name | Hajime Shimada |
| 4th Author's Affiliation | Nagoya University (Nagoya Univ.) |
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| Speaker | Author-1 |
| Date Time | 2019-11-13 14:20:00 |
| Presentation Time | 25 minutes |
| Registration for | ICSS |
| Paper # | ICSS2019-62 |
| Volume (vol) | vol.119 |
| Number (no) | no.288 |
| Page | pp.13-18 |
| #Pages | 6 |
| Date of Issue | 2019-11-06 (ICSS) |
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