Deteksi Serangan DDoS pada Jaringan Berbasis SDN dengan Klasifikasi Random Forest - Muhammad Khairullah Harto; Achmad Basuki (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2021)
Along with the development of network technology, threats related to the network are also growing, one of which is DDoS (Distributed Denial of Service). The increasingly advanced and affordable network infrastructure makes DDoS happen more and more. From year to year, there is a significant increase in the number of DDoS attack cases. Therefore, it is still necessary to study various algorithms for classifying data in networks that constitute deep DDoS. The SDN network was chosen because it has a simple implementation and does not require a lot of resources because of the information about the network topology and the controller that will be built using Ryu. The method used is the Random Forest algorithm as a method for classifying DDoS attacks. After conducting the research, the researchers found that Random Forest performed well in detecting DDoS attacks. The accuracy is quite high around 90% with an average detection time of 0.3 seconds.