A Prediction Model of DoS Attack's Distribution Discrete Probability

This paper describes the clustering problem first, and then utilizes the genetic algorithm to implement the optimization of clustering methods. Based on the optimized clustering on the sample data, we get various categories of the relation between traffics and attack amounts, and then builds up several prediction sub-models about DoS attack. Furthermore, according to the Bayesian method, we deduce discrete probability calculation about each sub-model and then get the distribution discrete probability prediction model for DoS attack.