An Improved Ant Colony Clustering Method for Network Intrusion Detection

Abstract

Intrusion detection is an important aspect of the network information safety. For the disadvantage that the existing intrusion detection method is not comprehensive of various kinds of attack and has lower detection rate and the higher fault detection rate, an improved ant colony clustering method for intrusion detection is proposed. The convergence rate of ant colony cluster algorithm is improved. In the optimization process, the information entropy is introduced to prevent into local optimal, and thus the method can adjust automatic the update pheromone and improve the clustering speed. And follow on, the intrusion detection system is designed. The experimental results show that the method is not only improves the detection rate, but reduced the fault detection rate, and can detection precisely the various kinds of attacks.