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Paper Abstract and Keywords
Presentation 2023-09-21 14:15
Studies on Malicious Domain Detection Method based on Feature of DNS Communication History by using DNS Traffic Analysis
Toshiki Koga, Daiki Nobayashi, Takeshi Ikenaga (KIT) IA2023-12
Abstract (in Japanese) (See Japanese page) 
(in English) Malware on the Internet is causing increasing damage, and countermeasures are needed. In some cases, malware-infected terminals use DNS when communicating with command and control (C&C) servers to obtain information for attacks. In previous study, a method to detect other malicious domains was proposed by focusing on the DNS communication history of malware-infected terminals and deriving co-occurrence relationships with known malicious domains based on the assumption that characteristic behaviors appear before and after communication with the C&C server. However, this method has a problem that the accuracy of detecting malignant domains varies greatly depending on the using data. In this paper, we discuss the impact on the accuracy of malicious domain detection by shortening the query domain name in the communication history to the primary domain name to make multiple domains common when calculating the characteristics of the behavior of each domain in the previous study. And to confirm the effectiveness of the proposed method, we apply the proposed method to a publicly available labeled dataset and evaluate the classification accuracy of the malignant and benign domains.
Keyword (in Japanese) (See Japanese page) 
(in English) DNS / Malware / Domain Name / Machine Learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 193, IA2023-12, pp. 6-10, Sept. 2023.
Paper # IA2023-12 
Date of Issue 2023-09-14 (IA) 
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 IA2023-12

Conference Information
Committee IA  
Conference Date 2023-09-21 - 2023-09-22 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univeristy 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Internet Operation and Management, Network Architecture, Communication Protocols, IoT, etc. 
Paper Information
Registration To IA 
Conference Code 2023-09-IA 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Studies on Malicious Domain Detection Method based on Feature of DNS Communication History by using DNS Traffic Analysis 
Sub Title (in English)  
Keyword(1) DNS  
Keyword(2) Malware  
Keyword(3) Domain Name  
Keyword(4) Machine Learning  
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Keyword(6)  
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1st Author's Name Toshiki Koga  
1st Author's Affiliation Kyushu Institute of Technology (KIT)
2nd Author's Name Daiki Nobayashi  
2nd Author's Affiliation Kyushu Institute of Technology (KIT)
3rd Author's Name Takeshi Ikenaga  
3rd Author's Affiliation Kyushu Institute of Technology (KIT)
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Speaker Author-1 
Date Time 2023-09-21 14:15:00 
Presentation Time 25 minutes 
Registration for IA 
Paper # IA2023-12 
Volume (vol) vol.123 
Number (no) no.193 
Page pp.6-10 
#Pages 5 
Date of Issue 2023-09-14 (IA) 

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