Journal of Information Processing
Online ISSN : 1882-6652
ISSN-L : 1882-6652
A Proposal of Highly Responsive Distributed Denial-of-Service Attacks Detection Using Real-Time Burst Detection Method
Shotaro UsuzakiYuki ArikawaHisaaki YamabaKentaro AburadaShin-Ichiro KubotaMirang ParkNaonobu Okazaki
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JOURNALS FREE ACCESS

2018 Volume 26 Pages 257-266

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Abstract

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.

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© 2018 by the Information Processing Society of Japan
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