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Paper Abstract and Keywords
Presentation 2017-03-03 10:40
Classification of Highly-Accurate Identifiable Applications Using Gini Index and Cosine Similarity
Takamitsu Iwai, Akihiro Nakao (UTokyo) NS2016-192
Abstract (in Japanese) (See Japanese page) 
(in English) Existing research on application identification has problems from three points of view; credibility of training data, flexibility of learning, and violation of privacy. Therefore, we propose a system that classifies mobile traffic using modified smartphones that send packets with application tags. This system has solved the problems mentioned above. We evaluate this system using a trace of real traffic and show this system can classify the 80% of the mobile only using the statistics of packets (e.g., the length of packets). We focus on applications that can be classified accurately using only destination IPs because they connect limited server. We propose the method that distinguishes these applications using Gini index and cosine similarity and classify mobile traffic sent by them accurately. We evaluate this method in real mobile traffic and show that we can classify 92% of about 14 applications traffic when learning period is set to 1 day.
Keyword (in Japanese) (See Japanese page) 
(in English) application identificaiton / machine learning / MVNO / / / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 484, NS2016-192, pp. 199-204, March 2017.
Paper # NS2016-192 
Date of Issue 2017-02-23 (NS) 
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 NS2016-192

Conference Information
Committee NS IN  
Conference Date 2017-03-02 - 2017-03-03 
Place (in Japanese) (See Japanese page) 
Place (in English) OKINAWA ZANPAMISAKI ROYAL HOTEL 
Topics (in Japanese) (See Japanese page) 
Topics (in English) General 
Paper Information
Registration To NS 
Conference Code 2017-03-NS-IN 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Classification of Highly-Accurate Identifiable Applications Using Gini Index and Cosine Similarity 
Sub Title (in English)  
Keyword(1) application identificaiton  
Keyword(2) machine learning  
Keyword(3) MVNO  
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1st Author's Name Takamitsu Iwai  
1st Author's Affiliation University of Tokyo (UTokyo)
2nd Author's Name Akihiro Nakao  
2nd Author's Affiliation University of Tokyo (UTokyo)
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Speaker Author-1 
Date Time 2017-03-03 10:40:00 
Presentation Time 20 minutes 
Registration for NS 
Paper # NS2016-192 
Volume (vol) vol.116 
Number (no) no.484 
Page pp.199-204 
#Pages 6 
Date of Issue 2017-02-23 (NS) 

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