Hierarchic Clustering Algorithm used for Anomaly Detecting

摘要

The popularity of using Internet contains some risks of network attacks. Intrusion detection is one major research problem in network security, whose aim is to prevent unauthorized access to system resources and data. This paper choose the clustering algorithm based on the hierarchical structure, to form normal behavior profile on the audit records and adjust the profile timely as the program behavior changed. The algorithm can convert the problem to resolve the problem of massive data processing to the hot research point of anomaly detection. Moreover, in order to improve the results of testing further, we choose data processing algorithm to get high-quality data source. As the experiment shown, we get effective experimental result.