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Paper Abstract and Keywords
Presentation 2021-12-17 11:00
IoT Device Identification based on Two-Stage Traffic Analysis
Chikako Takasaki, Tomohiro Korikawa, Kyota Hattori, Hidenari Oowada, Masafumi Shimizu, Naoki Takaya (NTT) NS2021-105
Abstract (in Japanese) (See Japanese page) 
(in English) Internet of Things (IoT) are used for various purposes, and many heterogenious sensors and devices is connected to networks. We need to control quality of service (QoS) and manage connected devices to optimize network rsources and topologies, but no method to manage a lot of devices simply at low cost has been established . One of the methods for managing a lot of devices is device estimation by analyzing communication protocols and system logs. However, communication protocols or formats of system logs of devices are different, and it is difficult to uniformly manage devices. Therefore, we need a method to identify devices efficiently. In this paper, we propose a method to identify manufacturers and function categories (e.g. cameras and speakers) of devices by analyzing network traffic in multi-stages. We identify manufacturers of devices and IoT by analyzing packet headers and payloads with machine learning. Then, we identify function categories of devices, which are identified as IoT in the previous stage, by analyzing traffic waveforms with deep learning. We evaluate the device identification performance with our method and show that our method can identify manufacturers and function categories of devices.
Keyword (in Japanese) (See Japanese page) 
(in English) Device identification / Traffic analysis / Machine learning / Deep learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 301, NS2021-105, pp. 47-51, Dec. 2021.
Paper # NS2021-105 
Date of Issue 2021-12-09 (NS) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
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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)
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Conference Information
Committee RCS NS  
Conference Date 2021-12-16 - 2021-12-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Nara-ken Bunka Kaikan and Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Multi-hop/Relay/Cooperation, Disaster-resistant wireless network, Sensor/Mesh network, Ad-hoc network, D2D/M2M, Wireless network coding, Handover/AP switching/Connected cell control/Load balancing among base stations/Mobile network dynamic reconfiguration, QoS/QoE assurance, Wireless VoIP, IoT, Edge computing, etc. 
Paper Information
Registration To NS 
Conference Code 2021-12-RCS-NS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) IoT Device Identification based on Two-Stage Traffic Analysis 
Sub Title (in English)  
Keyword(1) Device identification  
Keyword(2) Traffic analysis  
Keyword(3) Machine learning  
Keyword(4) Deep learning  
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1st Author's Name Chikako Takasaki  
1st Author's Affiliation NIPPON TELEGRAPH AND TELEPHONE CORPORATION (NTT)
2nd Author's Name Tomohiro Korikawa  
2nd Author's Affiliation NIPPON TELEGRAPH AND TELEPHONE CORPORATION (NTT)
3rd Author's Name Kyota Hattori  
3rd Author's Affiliation NIPPON TELEGRAPH AND TELEPHONE CORPORATION (NTT)
4th Author's Name Hidenari Oowada  
4th Author's Affiliation NIPPON TELEGRAPH AND TELEPHONE CORPORATION (NTT)
5th Author's Name Masafumi Shimizu  
5th Author's Affiliation NIPPON TELEGRAPH AND TELEPHONE CORPORATION (NTT)
6th Author's Name Naoki Takaya  
6th Author's Affiliation NIPPON TELEGRAPH AND TELEPHONE CORPORATION (NTT)
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Speaker Author-1 
Date Time 2021-12-17 11:00:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2021-105 
Volume (vol) vol.121 
Number (no) no.301 
Page pp.47-51 
#Pages
Date of Issue 2021-12-09 (NS) 


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