Detecting DDoS attack based on PSO Clustering algorithm
Xiaohong Hao, Boyu Meng, Kaicheng Gu · 2016
First, this article analyzes the Application layer Distributed Denial of Service(DDoS)'s attack principle and characteristic.According to the difference between normal users' browsing patterns and abnormal ones, user sessions are extracted from the web logs of normal users and similarities between different sessions are calculated .Because traditional K-mean Clustering algorithm is easy to fail into local optimal, the Particle Swarm Optimization K-mean Clustering algorithm is used to generate a detecting model.This model can been used to detect whether the undetermined sessions are DDoS attacks or not.The experiment show that this method can detect attacks effectively and have a good performance in adaptability.