Detection of the botnets’ low-rate DDoS attacks based on self-similarity

Sergii Lysenko, Kira Bobrovnikova, Serhii Matiukh, Ivan Hurman, Oleg Savenko

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.

Keywords


Botnet detection; Cyber attack; Hurst coefficient; Low-rate DDoS attack; Network traffic self-similarity

Full Text:

PDF


DOI: http://doi.org/10.11591/ijece.v10i4.pp%25p
Total views : 10 times

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.