Adaptive ant colony clustering method for intrusion detection

For the problem that partial data partition is not accurate enough in clustering results of ant colony clustering algorithm, an improved adaptive chaotic ant colony clustering algorithm based on information entropy is proposed.The algorithm measures the evolutive degree by optimizing the population information entropy,and adjusts the pheromone update strategy adaptively.It uses the chaotic search operator to search better solution near current global optimal solution at the end of each iteration.With progress of the algorithm,search range of the chaotic operator is gradually reduced so that chaotic operator avoids falling into local optimum in the initial period and improves search precision in the later period of ant colony search.This leads to better clustering results.Using the KDD Cup 1999 intrusion detection data,simulation results show that the clustering effect improves significantly,and can effectively improve the detection rate of intrusion detection and reduce the false detection rate.