@article{oai:ipsj.ixsq.nii.ac.jp:00186816,
 author = {Shotaro, Usuzaki and Yuki, Arikawa and Hisaaki, Yamaba and Kentaro, Aburada and Shin-Ichiro, Kubota and Mirang, Park and Naonobu, Okazaki and Shotaro, Usuzaki and Yuki, Arikawa and Hisaaki, Yamaba and Kentaro, Aburada and Shin-Ichiro, Kubota and Mirang, Park and Naonobu, Okazaki},
 issue = {3},
 journal = {情報処理学会論文誌},
 month = {Mar},
 note = {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
------------------------------, 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
------------------------------},
 title = {A Proposal of Highly Responsive Distributed Denial-of-Service Attacks Detection Using Real-Time Burst Detection Method},
 volume = {59},
 year = {2018}
}