基于量子遗传聚类的入侵检测方法*

现有基于聚类的入侵检测算法，聚类过程中需要预设聚类数，且算法的性能受初始数据输入顺序的影响，为此提出了一种新的基于量子遗传聚类入侵检测方法。该方法的基本思想是先自动建立初始聚类簇，再用改进量子遗传算法对初始聚类组合优化，最后进行入侵检测。实验结果表明，该方法能够有效地检测出网络中的入侵数据。

Intrusion detection algorithm based on quantum genetic clustering

The presented intrusion detection algorithm based on clustering need to know the cluster number before it works in clustering process. And the algorithm performance is decided by the order of input data. So, this paper proposed a new intrusion algorithm that based on quantum genetic clustering to solve the problems. The basic ideal of the algorithm was to create the initialization clusters with the cluster method, and then used the improved quantum genetic algorithm in the clusters combinatorial optimization.At last,used this method to detect intrusion. The experimental results demonstrate that this method can detect intrusion datas efficiently in the network environment.