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| Paper Abstract and Keywords | ||
| Presentation | 2024-02-29 11:35 Real-time Application Identification Scheme and Evaluation Method Using Machine Learning Tatsuhiro Ou, Kenji Kanai, Akihiro Nakao (Tokyo Univ.)  NS2023-189 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | With the diversification of mobile applications, the implementation of priority control that meets the communication requirements of each diversifying application and network slicing technology in 5G is awaited, and the need for Identifying the application names of traffic is increasing. This study introduces an operational scheme and performance evaluation methodology for real-time application identification, utilizing the high-accuracy and updatable application identification system demonstrated in the authors' previous research. We focus on the trade-off between buffer time and identification accuracy, present the effectiveness of the method from the perspective of future users, while providing analysis for the purpose of slicing for a specific application or communication type. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Mobile App Identification / Machine Learning / Random Forest / SSL/TLS / Traffic Analysis / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 123, no. 397, NS2023-189, pp. 103-108, Feb. 2024. | |
| Paper # | NS2023-189 | |
| Date of Issue | 2024-02-22 (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 | NS2023-189 |
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| Conference Information | |
| Committee | NS IN |
| Conference Date | 2024-02-29 - 2024-03-01 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Okinawa Convention Center |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | General |
| Paper Information | |
| Registration To | NS |
| Conference Code | 2024-02-NS-IN |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Real-time Application Identification Scheme and Evaluation Method Using Machine Learning |
| Sub Title (in English) | |
| Keyword(1) | Mobile App Identification |
| Keyword(2) | Machine Learning |
| Keyword(3) | Random Forest |
| Keyword(4) | SSL/TLS |
| Keyword(5) | Traffic Analysis |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Tatsuhiro Ou |
| 1st Author's Affiliation | The University of Tokyo (Tokyo Univ.) |
| 2nd Author's Name | Kenji Kanai |
| 2nd Author's Affiliation | The University of Tokyo (Tokyo Univ.) |
| 3rd Author's Name | Akihiro Nakao |
| 3rd Author's Affiliation | The University of Tokyo (Tokyo Univ.) |
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| Speaker | Author-1 |
| Date Time | 2024-02-29 11:35:00 |
| Presentation Time | 25 minutes |
| Registration for | NS |
| Paper # | NS2023-189 |
| Volume (vol) | vol.123 |
| Number (no) | no.397 |
| Page | pp.103-108 |
| #Pages | 6 |
| Date of Issue | 2024-02-22 (NS) |
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