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Paper Abstract and Keywords
Presentation 2019-11-02 15:25
Research on DNS tunnel detection by machine learning using appearance characters
Tetsuya Asakura, Takeo Tatsumi (OUJ) ISEC2019-84 SITE2019-78 LOIS2019-43
Abstract (in Japanese) (See Japanese page) 
(in English) In this study, as a detection technique of DNS tunnel, it was tried to detect abnormal DNS query string by machine learning (unsupervised learning) character string of normal domain name.
Using machine learning algorithm (One-Class SVM) of Python 3 and scikit-learn, we made a program for learning and evaluation, and confirmed it.
In the confirmation, the change of each evaluation value was compared on each machine learning model in increasing the learning number.
And, the time for learning and evaluation of the machine learning model was measured.
We discussed the experiment contents and results.
In our study, we confirmed that the machine learning model, which was confirmed by increasing the number of learning, has almost constant accuracy 0.977, precision 0.999, recall 0.958, and f1 score 0.978.
Keyword (in Japanese) (See Japanese page) 
(in English) DNS Tunnel / DNS Tunneling / Machine learning / Unsupervised learning / One-Class SVM / Domain Name / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 257, ISEC2019-84, pp. 141-148, Nov. 2019.
Paper # ISEC2019-84 
Date of Issue 2019-10-25 (ISEC, SITE, LOIS) 
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 ISEC2019-84 SITE2019-78 LOIS2019-43

Conference Information
Committee ISEC SITE LOIS  
Conference Date 2019-11-01 - 2019-11-02 
Place (in Japanese) (See Japanese page) 
Place (in English) Osaka Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To ISEC 
Conference Code 2019-11-ISEC-SITE-LOIS 
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)  
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  
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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 2019-11-02 15:25:00 
Presentation Time 25 minutes 
Registration for ISEC 
Paper # ISEC2019-84, SITE2019-78, LOIS2019-43 
Volume (vol) vol.119 
Number (no) no.257(ISEC), no.258(SITE), no.259(LOIS) 
Page pp.141-148 
#Pages 8 
Date of Issue 2019-10-25 (ISEC, SITE, LOIS) 

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