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Multiple-Features-Based Semisupervised Clustering DDoS Detection Method
Joint Authors
Yang, Zhen
Gu, Yonghao
Wang, Yongfei
Xiong, Fei
Gao, Yimu
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-17
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
DDoS attack stream from different agent host converged at victim host will become very large, which will lead to system halt or network congestion.
Therefore, it is necessary to propose an effective method to detect the DDoS attack behavior from the massive data stream.
In order to solve the problem that large numbers of labeled data are not provided in supervised learning method, and the relatively low detection accuracy and convergence speed of unsupervised k-means algorithm, this paper presents a semisupervised clustering detection method using multiple features.
In this detection method, we firstly select three features according to the characteristics of DDoS attacks to form detection feature vector.
Then, Multiple-Features-Based Constrained-K-Means (MF-CKM) algorithm is proposed based on semisupervised clustering.
Finally, using MIT Laboratory Scenario (DDoS) 1.0 data set, we verify that the proposed method can improve the convergence speed and accuracy of the algorithm under the condition of using a small amount of labeled data sets.
American Psychological Association (APA)
Gu, Yonghao& Wang, Yongfei& Yang, Zhen& Xiong, Fei& Gao, Yimu. 2017. Multiple-Features-Based Semisupervised Clustering DDoS Detection Method. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1190654
Modern Language Association (MLA)
Gu, Yonghao…[et al.]. Multiple-Features-Based Semisupervised Clustering DDoS Detection Method. Mathematical Problems in Engineering No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1190654
American Medical Association (AMA)
Gu, Yonghao& Wang, Yongfei& Yang, Zhen& Xiong, Fei& Gao, Yimu. Multiple-Features-Based Semisupervised Clustering DDoS Detection Method. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1190654
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190654