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アイテム
Lightweight Intrusion Detection Using Multiple Entropies of Traffic Behavior in IoT Networks
http://hdl.handle.net/10061/0002000144
http://hdl.handle.net/10061/000200014470cf3163-8875-4602-a10a-3e80d69ec7c0
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
fulltext (14.8 MB)
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| アイテムタイプ | 会議発表論文 / Conference Paper(1) | |||||||
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| 公開日 | 2024-03-21 | |||||||
| タイトル | ||||||||
| タイトル | Lightweight Intrusion Detection Using Multiple Entropies of Traffic Behavior in IoT Networks | |||||||
| 言語 | ||||||||
| 言語 | eng | |||||||
| 資源タイプ | ||||||||
| 資源タイプ | conference paper | |||||||
| 著者 |
Katsura, Yusei
× Katsura, Yusei
× 遠藤, 新× 垣内, 正年× 新井, イスマイル× 藤川, 和利 |
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| 抄録 | ||||||||
| 内容記述タイプ | Abstract | |||||||
| 内容記述 | Since Mirai malware first appeared in 2016, different variants have been created. The variants infect Internet of Things (IoT) devices such as home routers and webcams. The scale of DDoS attacks using Mirai-infected IoT devices has exceeded 600 Gbps. There has been a lot of researches on intrusion detection methods using machine learning for IoT networks. However, the existing method needs a lot of computational resources. Therefore, it is difficult to run such intrusion detection systems on resource-limited IoT gateways. In this research, we focus on the communication behavior of IoT devices, such as periodic communication with a specific server during benign operations. We propose a new intrusion detection method that represents the communication behavior of each host using multiple entropy features such as destination port number, source port number, and transmission time interval. The proposed method can achieve performance comparable to the existing intrusion detection method even if using a lightweight machine learning algorithm with fewer features. The evaluation of the results shows that the proposed method can reduce the detection processing time by 28.7 ms and memory usage by up to 331 MiB compared to the existing method, and the proposed method can achieve a detection accuracy of 99.8%, which is almost the same as the existing method. | |||||||
| 書誌情報 |
en : 2022 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT) 発行日 2023-01-25 |
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| 会議情報 | ||||||||
| 会議名 | 2022 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT) | |||||||
| 開始年 | 2022 | |||||||
| 開始月 | 12 | |||||||
| 開始日 | 18 | |||||||
| 終了年 | 2022 | |||||||
| 終了月 | 12 | |||||||
| 終了日 | 21 | |||||||
| 開催地 | Alamein New City | |||||||
| 開催国 | EGY | |||||||
| 出版者 | ||||||||
| 出版者 | IEEE | |||||||
| 出版者版DOI | ||||||||
| 関連タイプ | isVersionOf | |||||||
| 識別子タイプ | DOI | |||||||
| 関連識別子 | https://doi.org/10.1109/GCAIoT57150.2022.10019223 | |||||||
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| 関連タイプ | isVersionOf | |||||||
| 識別子タイプ | URI | |||||||
| 関連識別子 | https://ieeexplore.ieee.org/document/10019223 | |||||||
| 権利 | ||||||||
| 権利情報 | $00A9 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. 出版社許諾条件により、本文は2025年1月25日以降に公開 | |||||||
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| 出版タイプ | AM | |||||||
