Abstract
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.
Author supplied keywords
Cite
CITATION STYLE
Lysenko, S., Bobrovnikova, K., Matiukh, S., Hurman, I., & Savenko, O. (2020). Detection of the botnets’ low-rate DDoS attacks based on self-similarity. International Journal of Electrical and Computer Engineering, 10(4), 3651–3659. https://doi.org/10.11591/ijece.v10i4.pp3651-3659
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.