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| Paper Abstract and Keywords | ||
| Presentation | 2020-03-11 11:20 Applying Machine Learning to Malware Detection in Mobile Applications Yoshiki Kusama, Keiji Takeda, Kazuma Kobayashi, Osamu Nakamura (Keio Univ.), Lee Myoungje (LINE corp.)  IT2019-112 ISEC2019-108 WBS2019-61 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this paper, we proposed and implemented a detection method that focuses on a binary file stored in an APK(Android application package) as a feature in the construction of a learning model. There are slight differences in binary files. In this research, we focused on the difference, extracted the compiler information based on Yara, and applied it to 6 types of learning algorithms including MLP. Then, the model constructed by combining the features constructed with the three feature quantities(Permissions, Attribute, system call) and the compiler information was evaluated by accuracy, F-measure, and false detection rate. As a result, the model combining the compiler information improved the accuracy and F-measure and reduced the false detection rate. These results proved to be an effective feature for mobile malware detection. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Android / Mobile Security / Malware Detection / Header / Machine Learning / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 474, ISEC2019-108, pp. 151-157, March 2020. | |
| Paper # | ISEC2019-108 | |
| Date of Issue | 2020-03-03 (IT, ISEC, WBS) | |
| ISSN | Print edition: ISSN 0913-5685 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 | IT2019-112 ISEC2019-108 WBS2019-61 |
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| Conference Information | |
| Committee | ISEC IT WBS |
| Conference Date | 2020-03-10 - 2020-03-11 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | University of Hyogo |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | joint meeting of IT, ISEC, and WBS |
| Paper Information | |
| Registration To | ISEC |
| Conference Code | 2020-03-ISEC-IT-WBS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Applying Machine Learning to Malware Detection in Mobile Applications |
| Sub Title (in English) | |
| Keyword(1) | Android |
| Keyword(2) | Mobile Security |
| Keyword(3) | Malware Detection |
| Keyword(4) | Header |
| Keyword(5) | Machine Learning |
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| Keyword(8) | |
| 1st Author's Name | Yoshiki Kusama |
| 1st Author's Affiliation | Keio University (Keio Univ.) |
| 2nd Author's Name | Keiji Takeda |
| 2nd Author's Affiliation | Keio University (Keio Univ.) |
| 3rd Author's Name | Kazuma Kobayashi |
| 3rd Author's Affiliation | Keio University (Keio Univ.) |
| 4th Author's Name | Osamu Nakamura |
| 4th Author's Affiliation | Keio University (Keio Univ.) |
| 5th Author's Name | Lee Myoungje |
| 5th Author's Affiliation | LINE Corporation (LINE corp.) |
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| Speaker | Author-1 |
| Date Time | 2020-03-11 11:20:00 |
| Presentation Time | 25 minutes |
| Registration for | ISEC |
| Paper # | IT2019-112, ISEC2019-108, WBS2019-61 |
| Volume (vol) | vol.119 |
| Number (no) | no.473(IT), no.474(ISEC), no.475(WBS) |
| Page | pp.151-157 |
| #Pages | 7 |
| Date of Issue | 2020-03-03 (IT, ISEC, WBS) |
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