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Paper Abstract and Keywords
Presentation 2021-10-15 16:50
Malware Traffic Detection at Certain Time Using IP Flow Information
Seiya Komatsu, Yusei Katsura, Masatoshi Kakiuchi, Ismail Arai, Kazutoshi Fujikawa (NAIST) IA2021-27
Abstract (in Japanese) (See Japanese page) 
(in English) The damage caused by the activities of malware such as botnets and ransomware has become a social problem. In order to detect malware activity efficiently and reduce the damage, research on detecting malware activity traffic in the network has been proposed. There are three types of traffic information used in these research: packet information, IP flow information, and interface counters information. In the case of using IP flow information, traffic is aggregated in 5-tuples, which is lightweight, but the information is not output until a timeout occurs or the connection is terminated. Therefore, making it difficult to detect scanning activities or long-lasting flows at an early stage.
This research aims to maintain the same detection performance as conventional research by modifying the feature while detecting these flows before they terminate. In this paper, we experiment with existing methods that use connection status, port numbers, and transport layer protocols transition of each flow as features. We used the ISCX botnet dataset converted into IP flow information using Zeek to investigate the detection performance when the upper limit of flow duration is not set (the longest flow in the dataset: 240,418 seconds) and when the upper limit is set to 30 seconds. As a result, we confirmed that detection was possible with an F-measure of 98.1% and 96.1%, respectively. From this research, we showed that it is possible to detect malware traffic within 30 seconds (a certain time) with a slight decrease in detection performance.
Keyword (in Japanese) (See Japanese page) 
(in English) Malware / Botnet / Malware Detection / Intrusion Detection / Network Security / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 201, IA2021-27, pp. 6-11, Oct. 2021.
Paper # IA2021-27 
Date of Issue 2021-10-08 (IA) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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)
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Conference Information
Committee IA  
Conference Date 2021-10-15 - 2021-10-15 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Network R&D Testbed Operation and Utilization, etc. (cosponsored by ADVNET
Paper Information
Registration To IA 
Conference Code 2021-10-IA 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Malware Traffic Detection at Certain Time Using IP Flow Information 
Sub Title (in English)  
Keyword(1) Malware  
Keyword(2) Botnet  
Keyword(3) Malware Detection  
Keyword(4) Intrusion Detection  
Keyword(5) Network Security  
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Keyword(7)  
Keyword(8)  
1st Author's Name Seiya Komatsu  
1st Author's Affiliation Nara Institute of Science and Technology (NAIST)
2nd Author's Name Yusei Katsura  
2nd Author's Affiliation Nara Institute of Science and Technology (NAIST)
3rd Author's Name Masatoshi Kakiuchi  
3rd Author's Affiliation Nara Institute of Science and Technology (NAIST)
4th Author's Name Ismail Arai  
4th Author's Affiliation Nara Institute of Science and Technology (NAIST)
5th Author's Name Kazutoshi Fujikawa  
5th Author's Affiliation Nara Institute of Science and Technology (NAIST)
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Speaker Author-1 
Date Time 2021-10-15 16:50:00 
Presentation Time 25 minutes 
Registration for IA 
Paper # IA2021-27 
Volume (vol) vol.121 
Number (no) no.201 
Page pp.6-11 
#Pages
Date of Issue 2021-10-08 (IA) 


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