| Presentation | 2024-02-29 Intrusion Detection System Based on Federated Decision Trees Naoto Watanabe, Taku Yamazaki, Takumi Miyoshi, Masataka Nakahara, Norihiro Okui, Ayumu Kubota, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | With the proliferation of Internet of things (IoT) devices, cyberattacks targeting these devices have also been increasing. In 2016, a distributed denial of service (DDoS) attack was conducted by a botnet composed of IoT devices infected with the Mirai malware, and traffic caused by the attack was observed to be up to 1.5Tbps. In addition, new variants of malware are still being discovered, and unknown attacks by them are expected in the future. Generally, cyberattacks are observed from various locations because attacks targeting IoT devices are aimed at random hosts on the internet. Therefore, it is possible to detect the unknown attacks by using the unknown attack information collected at another location. This paper proposes an intrusion detection system that dynamically responds to unknown attacks by performing federated learning based on decision trees using traffic collected by multipoint gateways. Experimental results with actual traffic collected using IoT devices and honeypots clarify the effectiveness of the proposed system. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | IoT / Machine learning / Federated learning / Honeypot / Intrusion detection |
| Paper # | NS2023-190 |
| Date of Issue | 2024-02-22 (NS) |
| Conference Information | |
| Committee | NS / IN |
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| Conference Date | 2024/2/29(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Okinawa Convention Center |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | General |
| Chair | Tetsuya Oishi(NTT) / Kunio Hato(NTT) |
| Vice Chair | Takumi Miyoshi(Shibaura Inst. of Tech.) / Tsutomu Murase(Nagoya Univ.) |
| Secretary | Takumi Miyoshi(NTT) / Tsutomu Murase(Kogakuin Univ.) |
| Assistant | Hiroshi Yamamoto(NTT) |
| Paper Information | |
| Registration To | Technical Committee on Network Systems / Technical Committee on Information Networks |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Intrusion Detection System Based on Federated Decision Trees |
| Sub Title (in English) | |
| Keyword(1) | IoT |
| Keyword(2) | Machine learning |
| Keyword(3) | Federated learning |
| Keyword(4) | Honeypot |
| Keyword(5) | Intrusion detection |
| 1st Author's Name | Naoto Watanabe |
| 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.) |
| 4th Author's Name | Masataka Nakahara |
| 4th Author's Affiliation | KDDI Research, Inc.(KDDI Research) |
| 5th Author's Name | Norihiro Okui |
| 5th Author's Affiliation | KDDI Research, Inc.(KDDI Research) |
| 6th Author's Name | Ayumu Kubota |
| 6th Author's Affiliation | KDDI Research, Inc.(KDDI Research) |
| Date | 2024-02-29 |
| Paper # | NS2023-190 |
| Volume (vol) | vol.123 |
| Number (no) | NS-397 |
| Page | pp.pp.109-112(NS), |
| #Pages | 4 |
| Date of Issue | 2024-02-22 (NS) |