DDOS Attack Detection Accuracy Improvement in Software Defined Network (SDN) Using Ensemble Classification

Shirmarz A., Ghaffari A., Mohammadi R., Akleylek S.

14th International Conference on Information Security and Cryptology, ISCTURKEY 2021, Ankara, Türkiye, 2 - 03 Aralık 2021, ss.111-115 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/iscturkey53027.2021.9654403
  • Basıldığı Şehir: Ankara
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.111-115
  • Anahtar Kelimeler: accuracy, DDOS attack, POX controller, SDN
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

Nowadays, Denial of Service (DOS) is a significant cyberattack that can happen on the Internet. This attack can be taken place with more than one attacker that in this case called Distributed Denial of Service (DDOS). The attackers endeavour to make the resources (server & bandwidth) unavailable to legitimate traffic by overwhelming resources with malicious traffic. An appropriate security module is needed to discriminate the malicious flows with high accuracy to prevent the failure resulting from a DDOS attack. In this paper, a DDoS attack discriminator will be designed for Software Defined Network (SDN) architecture so that it can be deployed in the POX controller. The simulation results present that the proposed model can achieve an accuracy of about 99.4%which shows an outstanding percentage of improvement compared with Decision Tree (DT), K-Nearest Neighbour (KNN), Support Vector Machine (SVM) approaches.