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| Presentation | 2020-03-10 13:25 Research on DNS tunnel detection by machine learning using appearance characters -- Consideration of implementation of evaluation program -- Tetsuya Asakura, Takeo Tatsumi (OUJ)  IT2019-103 ISEC2019-99 WBS2019-52 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this study, we considered an implementation a detection technique of DNS tunnel. This detection techniqe is likely to can detect abnormal DNS query string by machine learning (unsupervised learning) character string of normal domain name. Therefore we tested and experimented an implementation evaluation program for real environment. Using machine learning algorithm (One-Class SVM) of Python 3 and scikit-learn, we made a program for evaluation, and tested in real environment. In implementation test, we deployed an evaluation program in PC of real environment, and confirmed to normal it. While to runed evaluation program, we got DNS query for DNS packets. We discussed the implementation test, experiment, and results. In this study, we confirmed that the machine learning model in evaluation program, enable normal detection greater than 97 percent. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | DNS Tunnel / DNS Tunneling / Machine learning / Unsupervised learning / One-Class SVM / Domain Name / Internationalized Domain Name / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 474, ISEC2019-99, pp. 87-94, March 2020. | |
| Paper # | ISEC2019-99 | |
| 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 | IT2019-103 ISEC2019-99 WBS2019-52 |
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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) | Research on DNS tunnel detection by machine learning using appearance characters |
| Sub Title (in English) | Consideration of implementation of evaluation program |
| Keyword(1) | DNS Tunnel |
| Keyword(2) | DNS Tunneling |
| Keyword(3) | Machine learning |
| Keyword(4) | Unsupervised learning |
| Keyword(5) | One-Class SVM |
| Keyword(6) | Domain Name |
| Keyword(7) | Internationalized Domain Name |
| Keyword(8) | |
| 1st Author's Name | Tetsuya Asakura |
| 1st Author's Affiliation | The Open University of Japan (OUJ) |
| 2nd Author's Name | Takeo Tatsumi |
| 2nd Author's Affiliation | The Open University of Japan (OUJ) |
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| Speaker | Author-1 |
| Date Time | 2020-03-10 13:25:00 |
| Presentation Time | 25 minutes |
| Registration for | ISEC |
| Paper # | IT2019-103, ISEC2019-99, WBS2019-52 |
| Volume (vol) | vol.119 |
| Number (no) | no.473(IT), no.474(ISEC), no.475(WBS) |
| Page | pp.87-94 |
| #Pages | 8 |
| Date of Issue | 2020-03-03 (IT, ISEC, WBS) |
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