文章基本信息

标题：Detection of the botnets’ low-rate DDoS attacks based on self-similarity
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作者：Sergii Lysenko ; Kira Bobrovnikova ; Serhii Matiukh 等
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2020
卷号：10
期号：4
页码：3651-3659
DOI：10.11591/ijece.v10i4.pp3651-3659
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：An article presents the approach for the botnets’ low-rate a DDoS-attacks detection based on the botnet’s behavior in the network. Detection process involves the analysis of the network traffic, generated by the botnets’ low-rate DDoS attack. Proposed technique is the part of botnets detection system – BotGRABBER system. The novelty of the paper is that the low-rate DDoS-attacks detection involves not only the network features, inherent to the botnets, but also network traffic self-similarity analysis, which is defined with the use of Hurst coefficient. Detection process consists of the knowledge formation based on the features that may indicate low-rate DDoS attack performed by a botnet; network monitoring, which analyzes information obtained from the network and making conclusion about possible DDoS attack in the network; and the appliance of the security scenario for the corporate area network’s infrastructure in the situation of low-rate attacks.
关键词：Botnet detection;Cyber attack;Hurst coefficient;Low-rate DDoS attack;Network traffic self-similarity