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Paper Abstract and Keywords
Presentation 2013-03-08 14:50
A Study on Malware Traffic Detection by Using N-gram Probability Density
Kenji Kawamoto (Waseda Univ.), Masatsugu Ichino, Yusuke Otsuki (Univ. of Electro-Comm.), Mitsuhiro Hatada (NTT), Hiroshi Yoshiura (Univ. of Electro-Comm.), Jiro Katto (Waseda Univ.) LOIS2012-102
Abstract (in Japanese) (See Japanese page) 
(in English) The threat of malware is increasing.
Malware detection has thus become important for the safety of the Internet usage.
In this paper,
our goal is to classify Internet traffic into normal or anomalous class correctly to prevent malware from spreading through the Internet.
To stop malware, we are focusing on the time series changes between normal and malware traffic.
We propose a malware detection method by using N-gram to handle time series changes.
Classification of Internet traffic into normal or anomoalous class is done by using posterior probability calculated by nearest neighbor density estimation.
We use CCCDATAset2010,2011 as malware traffic,
and application traffic captured dby a PC as normal traffic.
Keyword (in Japanese) (See Japanese page) 
(in English) malware detection / pattern recognition / N-gram / nearest neighbor density estimation / / / /  
Reference Info. IEICE Tech. Rep., vol. 112, no. 466, LOIS2012-102, pp. 191-196, March 2013.
Paper # LOIS2012-102 
Date of Issue 2013-02-28 (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 LOIS2012-102

Conference Information
Committee LOIS  
Conference Date 2013-03-07 - 2013-03-08 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To LOIS 
Conference Code 2013-03-LOIS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Malware Traffic Detection by Using N-gram Probability Density 
Sub Title (in English)  
Keyword(1) malware detection  
Keyword(2) pattern recognition  
Keyword(3) N-gram  
Keyword(4) nearest neighbor density estimation  
Keyword(5)  
Keyword(6)  
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Keyword(8)  
1st Author's Name Kenji Kawamoto  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Masatsugu Ichino  
2nd Author's Affiliation The University of Electro-Communications (Univ. of Electro-Comm.)
3rd Author's Name Yusuke Otsuki  
3rd Author's Affiliation The University of Electro-Communications (Univ. of Electro-Comm.)
4th Author's Name Mitsuhiro Hatada  
4th Author's Affiliation NTT Communications Corporation (NTT)
5th Author's Name Hiroshi Yoshiura  
5th Author's Affiliation The University of Electro-Communications (Univ. of Electro-Comm.)
6th Author's Name Jiro Katto  
6th Author's Affiliation Waseda University (Waseda Univ.)
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Speaker Author-1 
Date Time 2013-03-08 14:50:00 
Presentation Time 20 minutes 
Registration for LOIS 
Paper # LOIS2012-102 
Volume (vol) vol.112 
Number (no) no.466 
Page pp.191-196 
#Pages 6 
Date of Issue 2013-02-28 (LOIS) 

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