Abstract：An algorithm of finding distance-based outlier （Cell-Based） was studied. Its disadvantages were pointed out. An algorithm of intrusion detection based on kernel mapping was proposed, which could detect intrusion by finding outliers. The data point was mapped from the original space to a high-dimensional feature kernel space by kernel function, and the distance between the data points was redefined. After initial clustering processing, the number of clusters and the original cluster centers were obtained. Through iterative processing for modified objective function, reclustering of data points was realized. Those points which were out of the cluster centers＇ radius were the outliers. Experiments showed that the data points are more separable in this algorithm. The algorithm can overcome the faults of traditional Cell-Based algorithm, which need to be recomputed from the scratch for every change of the parameters. It also has higher detection rate at higher convergence speed.
殷新春, 葛邮兵. 一种基于核映射空间距离的入侵检测算法[J]. 江苏大学学报（自然科学版）, 2008, 29(5): 437-440.
Yin Xinchun, Ge Youbing. An algorithm of intrusion detection based on kernel mapping[J]. Journal of Jiangsu University(Natural Science Eidtion)
, 2008, 29(5): 437-440.
2008, Vol. 29 
