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Paper Abstract and Keywords
Presentation 2015-09-04 10:35
[Encouragement Talk] Identification of Mobile Applications via In-Network Machine Learning Using N-gram for Application-Specific Traffic Control
Takamitsu Iwai, Akihiro Nakao (UTokyo) NS2015-78
Abstract (in Japanese) (See Japanese page) 
(in English) Identifying the application transmitting a given flow of network traffic is beneficial for network management, especially for achieving application specific QoS, enabling malware detection, and executing network functions such as content caching only for a particular application.
Although typical methods for application identification include port scanning and pattern recognition using application signature,
they suffer from various problems, e.g., for the former, ephemeral port usage and dynamic port allocation hinder accurate
application identification, and for the latter, it is costly to collect application signatures, especially from encrypted traffic.
The existing research for application identification using machine learning have shortcomings such as a limited scope of identifiable applications,
inability to deal with real-time traffic, and few efforts have been put to fine-grained application identification, e.g., at the level of application
identifiers such as YouTube and Chrome. We have proposed a real-time identification method using reliable
and on-line training data collection performed by adding the application identifier at the end of the SYN packet.
Our existing method identifies 80% mobile applications accurately without Deep Packet Inspection (DPI).
In this paper, we propose a new method that improves inference accuracy using DPI even applicable to encrypted traffic.
We evaluate our method in real MVNO traffic and show our method identifies at maximum 92% applications in the traffic
accurately using 2-gram features of packet payloads. We also improve the inference accuracy from 82% without DPI to 90 % with DPI
when learning period is limited to 5 days.
Keyword (in Japanese) (See Japanese page) 
(in English) application identification / machine learning / SDN / NFV / MVNO / mobile edge computing / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 209, NS2015-78, pp. 41-46, Sept. 2015.
Paper # NS2015-78 
Date of Issue 2015-08-27 (NS) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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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)
Download PDF NS2015-78

Conference Information
Committee IN NS CS NV  
Conference Date 2015-09-03 - 2015-09-04 
Place (in Japanese) (See Japanese page) 
Place (in English) Iwate-ken Kokaido 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Post IP networking, Next Generation Network (NGN)/New Generation Network (NWGN), Contingency Plan/BCP, Network Coding/Network Algorithms, Session Management (SIP/IMS), Internetworking/Standardization, Network configuration, etc. 
Paper Information
Registration To NS 
Conference Code 2015-09-IN-NS-CS-NV 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Identification of Mobile Applications via In-Network Machine Learning Using N-gram for Application-Specific Traffic Control 
Sub Title (in English)  
Keyword(1) application identification  
Keyword(2) machine learning  
Keyword(3) SDN  
Keyword(4) NFV  
Keyword(5) MVNO  
Keyword(6) mobile edge computing  
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Keyword(8)  
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
Date Time 2015-09-04 10:35:00 
Presentation Time 25 
Registration for NS 
Paper # IEICE-NS2015-78 
Volume (vol) IEICE-115 
Number (no) no.209 
Page pp.41-46 
#Pages IEICE-6 
Date of Issue IEICE-NS-2015-08-27 


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