| Presentation | 2021-09-09 A Machine Learning Based Network Intrusion Detection System with Appling Different Algorithms in Multiple Stages Seiichi Sasa, Hiroyuki Suzuki, Akio Koyama, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In recent years, the rapid development of Information and Communication Technology (ICT) has led to the provision of a wide variety of network services. Along with this, the current situation is that cyber attacks that interfere with these services occur frequently and the damage is increasing. Therefore, there is a need to strengthen countermeasures against cyber-attacks and to minimize damage by responding quickly and with high accuracy. Therefore, in order to enhance security measures in network environments, a lot of research has been conducted to improve the performance of intrusion detection systems by applying machine learning to them. However, there are many false positives, and machine learning is not yet able to classify and detect them completely. In this study, we aimed to reduce the number of false positives by applying different machine learning algorithms to the intrusion detection system in multiple stages. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Machine Learning / Cyber Attack / Intrusion Detection System / Security |
| Paper # | NS2021-63 |
| Date of Issue | 2021-09-02 (NS) |
| Conference Information | |
| Committee | IN / NS / CS |
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| Conference Date | 2021/9/9(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Session management (SIP/IMS), Interoperability/Standardization, NGN/NwGN/Future networks, Cloud/Data center networks, SDN (OpenFlow, etc.)/NFV, IPv6, Machine learning, etc. |
| Chair | Kenji Ishida(Hiroshima City Univ.) / Akihiro Nakao(Univ. of Tokyo) / Jun Terada(NTT) |
| Vice Chair | Kunio Hato(Internet Multifeed) / Tetsuya Oishi(NTT) / Daisuke Umehara(Kyoto Inst. of Tech.) |
| Secretary | Kunio Hato(NTT) / Tetsuya Oishi(Univ. of Nagasaki) / Daisuke Umehara(Nagaoka Univ. of Tech.) |
| Assistant | / Kotaro Mihara(NTT) / Takahiro Yamaura(Toshiba) / Yuta Ida(Yamaguchi Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Information Networks / Technical Committee on Network Systems / Technical Committee on Communication Systems |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Machine Learning Based Network Intrusion Detection System with Appling Different Algorithms in Multiple Stages |
| Sub Title (in English) | |
| Keyword(1) | Machine Learning |
| Keyword(2) | Cyber Attack |
| Keyword(3) | Intrusion Detection System |
| Keyword(4) | Security |
| 1st Author's Name | Seiichi Sasa |
| 1st Author's Affiliation | Yamagata University(Yamagata Univ.) |
| 2nd Author's Name | Hiroyuki Suzuki |
| 2nd Author's Affiliation | Yamagata University(Yamagata Univ.) |
| 3rd Author's Name | Akio Koyama |
| 3rd Author's Affiliation | Yamagata University(Yamagata Univ.) |
| Date | 2021-09-09 |
| Paper # | NS2021-63 |
| Volume (vol) | vol.121 |
| Number (no) | NS-170 |
| Page | pp.pp.36-41(NS), |
| #Pages | 6 |
| Date of Issue | 2021-09-02 (NS) |