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| Paper Abstract and Keywords | ||
| Presentation | 2022-03-09 09:30 Unknown IoT Device Recognition Using Traffic Classification by Machine Learning Jun Motoyama, Takumi Miyoshi, Taku Yamazaki, Thomas Silverston (Shibaura Inst. Tech.)  CQ2021-100 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Internet of things (IoT) has become widespread, and it is predicted that the number of IoT devices will continue to increase. In response to this rapid proliferation, it is difficult to keep track of the status of a large number of IoT devices, which raises the issue of security. In previous research, many methods have been proposed to classify devices using machine learning for multiple devices, but few methods have been developed to predict or discover unknown devices using the resulting learning models. This paper proposes a method to classify unknown IoT devices by identifying the traffic generated by the devices using machine learning, assuming a network that many IoT devices are connected to. The experimental results show that the proposed method can classify devices without misrecognition in terms of security. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Machine learning / IoT / Device estimation / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 421, CQ2021-100, pp. 1-4, March 2022. | |
| Paper # | CQ2021-100 | |
| Date of Issue | 2022-03-02 (CQ) | |
| 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 | CQ2021-100 |
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| Conference Information | |
| Committee | CQ IMQ MVE IE |
| Conference Date | 2022-03-09 - 2022-03-11 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online (Zoom) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Media of five senses, Multimedia, Media experience, Picture codinge, Image media quality, Network,quality and reliability, etc |
| Paper Information | |
| Registration To | CQ |
| Conference Code | 2022-03-CQ-IMQ-MVE-IE |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Unknown IoT Device Recognition Using Traffic Classification by Machine Learning |
| Sub Title (in English) | |
| Keyword(1) | Machine learning |
| Keyword(2) | IoT |
| Keyword(3) | Device estimation |
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| 1st Author's Name | Jun Motoyama |
| 1st Author's Affiliation | Shibaura Institute of Technology (Shibaura Inst. Tech.) |
| 2nd Author's Name | Takumi Miyoshi |
| 2nd Author's Affiliation | Shibaura Institute of Technology (Shibaura Inst. Tech.) |
| 3rd Author's Name | Taku Yamazaki |
| 3rd Author's Affiliation | Shibaura Institute of Technology (Shibaura Inst. Tech.) |
| 4th Author's Name | Thomas Silverston |
| 4th Author's Affiliation | Shibaura Institute of Technology (Shibaura Inst. Tech.) |
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| Speaker | Author-1 |
| Date Time | 2022-03-09 09:30:00 |
| Presentation Time | 25 minutes |
| Registration for | CQ |
| Paper # | CQ2021-100 |
| Volume (vol) | vol.121 |
| Number (no) | no.421 |
| Page | pp.1-4 |
| #Pages | 4 |
| Date of Issue | 2022-03-02 (CQ) |
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