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Paper Abstract and Keywords
Presentation 2024-10-10 10:50
Comparison and Evaluation of Two-stage Clustering Methods for IoT Device Identification in Real Environments
Mizuki Asano, Taku Yamazaki, Takumi Miyoshi (Shibaura Inst. Tech.) NS2024-100
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, smart homes have garnered increasing attention for their potential to enhance efficiency and comfort through the use of Internet of things (IoT) and Artificial intelligence (AI) technologies. However, security concerns persist, due to challenges related to IoT device updates, firmware upgrades, and the complexities of deploying large-scale systems. To address these issues, various machine learning-based methods for identifying IoT devices through traffic data have been proposed. In our previous research, we introduced an IoT traffic analysis and device identification method based on two-stage clustering in real environments, demonstrating its effectiveness in terms of both identification accuracy and processing efficiency. However, the application of k-means and single clustering algorithms in the two-stage clustering method has not been thoroughly investigated. In this paper, we conduct a comparative evaluation of two-stage clustering methods for IoT device identification in real environments. We implement two-stage clustering methods using various combinations of clustering algorithms and evaluate them from the perspectives of clustering performance and processing overhead in traffic analysis.
Keyword (in Japanese) (See Japanese page) 
(in English) IoT / traffic analysis / machine learning / clustering / device identification / smart home / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 197, NS2024-100, pp. 52-57, Oct. 2024.
Paper # NS2024-100 
Date of Issue 2024-10-02 (NS) 
ISSN 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 NS2024-100

Conference Information
Committee NS  
Conference Date 2024-10-09 - 2024-10-11 
Place (in Japanese) (See Japanese page) 
Place (in English) Tokushima University + Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Network architecture (5G, Local 5G, Beyond5G, Mobile networks, Ad-hoc and sensor networks, Overlay and P2P networks, Programmable networks, SDN/NFV, IoT, Network slicing), Next generation packet transport (High speed Ethernet, IP over WDM, Multi-service package technology, MPLS), Grid, etc. 
Paper Information
Registration To NS 
Conference Code 2024-10-NS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Comparison and Evaluation of Two-stage Clustering Methods for IoT Device Identification in Real Environments 
Sub Title (in English)  
Keyword(1) IoT  
Keyword(2) traffic analysis  
Keyword(3) machine learning  
Keyword(4) clustering  
Keyword(5) device identification  
Keyword(6) smart home  
Keyword(7)  
Keyword(8)  
1st Author's Name Mizuki Asano  
1st Author's Affiliation Shibaura Institute of Technology (Shibaura Inst. Tech.)
2nd Author's Name Taku Yamazaki  
2nd Author's Affiliation Shibaura Institute of Technology (Shibaura Inst. Tech.)
3rd Author's Name Takumi Miyoshi  
3rd Author's Affiliation Shibaura Institute of Technology (Shibaura Inst. Tech.)
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Speaker Author-1 
Date Time 2024-10-10 10:50:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2024-100 
Volume (vol) vol.124 
Number (no) no.197 
Page pp.52-57 
#Pages 6 
Date of Issue 2024-10-02 (NS) 

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