Anomaly Based Distributed Denial of Service Attack Detection and Prevention with Machine Learning

Dincalp U., GÜZEL M. S., SEVİNÇ Ö., BOSTANCI G. E., Askerzade İ.

2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), Kizilcahamam, Türkiye, 19 - 21 Ekim 2018, ss.600-603 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/ismsit.2018.8567252
  • Basıldığı Şehir: Kizilcahamam
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.600-603
  • Anahtar Kelimeler: ddos attack, DBSCAN, machine learning
  • Ankara Üniversitesi Adresli: Evet

Özet

Everyday, the DoS/DDoS attacks are increasing all over the world and the ways attackers are using changing continuously. This increase and variety on the attacks are affecting the governments, institutions, organizations and corporations in a bad way. Every successful attack is causing them to lose money and lose reputation in return. This paper presents an introduction to a method which can show what the attack and where the attack based on. This is tried to be achieved with using clustering algorithm DBSCAN on network traffic because of the change and variety in attack vectors.