| Paper Abstract and Keywords |
| Presentation |
2022-05-19 10:25
BGP Hijacking Detection Using Deep Learning Kenta Nakashima, Mitiko Harayama (Gifu City Univ) ICM2022-2 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Failures of large autonomous systems (ASs) and network attacks can affect Border Gateway Protocol (BGP) messages, causing delays and instability in overall Internet communications. We note this as BGP hijacking and propose an anomaly detection method for BGP messages using deep learning. We report four incidents caused by Malaysia-Telekom, Level3, Google, and Facebook. We analyze BGP messages around the incidents to obtain nine features, such as AS path length statistics. These were trained on a multilayer perceptron (MLP) to determine the accuracy of incident detection. As a result, some of the features, such as new BGP announcements and withdrawals, change in conjunction with incidents. Detection accuracies for Malaysia-Telekom and Level 3 incidents were high. In this report, we show how to analyze the features of BGP messages, how they change, and the anomaly detection performance of our method. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
BGP / BGP Hijacking / Anomaly detection / Deep learning / / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 122, no. 32, ICM2022-2, pp. 6-11, May 2022. |
| Paper # |
ICM2022-2 |
| Date of Issue |
2022-05-12 (ICM) |
| 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 |
ICM2022-2 |
| Conference Information |
| Committee |
ICM IPSJ-CSEC IPSJ-IOT |
| Conference Date |
2022-05-19 - 2022-05-20 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
|
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
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| Paper Information |
| Registration To |
ICM |
| Conference Code |
2022-05-ICM-CSEC-IOT |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
BGP Hijacking Detection Using Deep Learning |
| Sub Title (in English) |
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| Keyword(1) |
BGP |
| Keyword(2) |
BGP Hijacking |
| Keyword(3) |
Anomaly detection |
| Keyword(4) |
Deep learning |
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| 1st Author's Name |
Kenta Nakashima |
| 1st Author's Affiliation |
Gifu City University (Gifu City Univ) |
| 2nd Author's Name |
Mitiko Harayama |
| 2nd Author's Affiliation |
Gifu City University (Gifu City Univ) |
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| Speaker |
Author-1 |
| Date Time |
2022-05-19 10:25:00 |
| Presentation Time |
25 minutes |
| Registration for |
ICM |
| Paper # |
ICM2022-2 |
| Volume (vol) |
vol.122 |
| Number (no) |
no.32 |
| Page |
pp.6-11 |
| #Pages |
6 |
| Date of Issue |
2022-05-12 (ICM) |