Research of Intrusion Detection Method Based on Ant Colony Clustering
Qiang Yue, Zhongyu Hu, Shikai Shen, Dawei Zhang · Advances in engineering research/Advances in Engineering Research · 2016
Network intrusion detection has been intensively investigated in recent years.In this paper, we propose an adaptive method based on ant colony clustering to discover unknown attacks.The focus of the method is the clustering process of an ant colony movement.The structure of the intrusion detection system based on ant colony clustering is designed.We use the KDD99 data set to design and evaluate our algorithm.The experimental results show the capability of our method successfully to detect network intrusions compared with the K-Means clustering algorithm.The method can not only improve the detection rate but also reduce false positive rate significantly，and can automatically detect various kinds of attacks.