A Proposal of Highly Responsive Distributed Denial-of-Service Attacks Detection Using Real-Time Burst Detection Method

• Item type: Journal(1)
• 公開日: 2018-03-15
• タイトル: A Proposal of Highly Responsive Distributed Denial-of-Service Attacks Detection Using Real-Time Burst Detection Method
• タイトル / 言語: en
• タイトル: A Proposal of Highly Responsive Distributed Denial-of-Service Attacks Detection Using Real-Time Burst Detection Method
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [特集：若手研究者] Distributed Denial-of-Service attack, real-time burst detection, highly responsive
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: Graduate School of Computer Science and Systems Engineering, University of Miyazaki
• 著者所属: Graduate School of Computer Science and Systems Engineering, University of Miyazaki
• 著者所属: Faculty of Engineering, University of Miyazaki
• 著者所属: Faculty of Engineering, University of Miyazaki
• 著者所属: Center for Management of Information Technologies, Kumamoto University
• 著者所属: Faculty of Information Technology, Kanagawa Institute of Technology
• 著者所属: Faculty of Engineering, University of Miyazaki
• 著者所属(英): en
• 著者所属(英): Graduate School of Computer Science and Systems Engineering, University of Miyazaki
• 著者所属(英): en
• 著者所属(英): Graduate School of Computer Science and Systems Engineering, University of Miyazaki
• 著者所属(英): en
• 著者所属(英): Faculty of Engineering, University of Miyazaki
• 著者所属(英): en
• 著者所属(英): Faculty of Engineering, University of Miyazaki
• 著者所属(英): en
• 著者所属(英): Center for Management of Information Technologies, Kumamoto University
• 著者所属(英): en
• 著者所属(英): Faculty of Information Technology, Kanagawa Institute of Technology
• 著者所属(英): en
• 著者所属(英): Faculty of Engineering, University of Miyazaki
• 著者名: Shotaro, Usuzaki; Yuki, Arikawa; Hisaaki, Yamaba; Kentaro, Aburada; Shin-Ichiro, Kubota; Mirang, Park; Naonobu, Okazaki
• 著者名(英): Shotaro, Usuzaki; Yuki, Arikawa; Hisaaki, Yamaba; Kentaro, Aburada; Shin-Ichiro, Kubota; Mirang, Park; Naonobu, Okazaki
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Distributed Denial-of-Service (DDoS) attack detection systems are classified into a signature based approach and an anomaly based approach. However, such methods tend to suffer from low responsiveness. On the other hand, real-time burst detection which is used in data mining offers two advantages over traditional statistical methods. First, it can be used for real-time detection when an event is occurring, and second, it can work with less processing as information about events are compressed, even if a large number of events occur. Here, the authors add the function for attack detection in real-time burst detection technique, and propose a highly responsive DDoS attack detection technique. This paper performs experiments to evaluate its effectiveness, and discusses its detection accuracy and processing performance.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.26(2018) (online); DOI http://dx.doi.org/10.2197/ipsjjip.26.257; ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Distributed Denial-of-Service (DDoS) attack detection systems are classified into a signature based approach and an anomaly based approach. However, such methods tend to suffer from low responsiveness. On the other hand, real-time burst detection which is used in data mining offers two advantages over traditional statistical methods. First, it can be used for real-time detection when an event is occurring, and second, it can work with less processing as information about events are compressed, even if a large number of events occur. Here, the authors add the function for attack detection in real-time burst detection technique, and propose a highly responsive DDoS attack detection technique. This paper performs experiments to evaluate its effectiveness, and discusses its detection accuracy and processing performance.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.26(2018) (online); DOI http://dx.doi.org/10.2197/ipsjjip.26.257; ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 59, 号 3, 発行日 2018-03-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764