数据流挖掘算法在网络安全中的应用研究

入侵检测技术是网络安全中的核心技术,把数据流中频繁项集的挖掘应用于入侵检测系统中正常和异常数据分析已是当前网络安全中的一个重要发展方向.流入网络流中的数据高速并且无限到达,所以利用传统多遍扫描数据库的挖掘技术来构建入侵检测模型已受到局限.针对频繁模式多维的特点,提出了一种新型数据结构SW.Tree,并给出了一种高效的挖掘网络访问数据流的挖掘算法,把这种算法应用于网络入侵检测模型中频繁模式的挖掘,取得了较好的成效.

The Application Research of Data Stream Mining Algorithms in Network Security

The technology of intrusion detection is the core of network security technology. Frequent itemset mining in the data streams is used in normal and abnormal data analysis of intrusion detection system,which is an important direction in development of the current network security. Network data are always high-speed and unlimited. Typical data mining methods, which always do multi-scanning to databases, do not fit in with construc- ting intrusion detection model for high-speed network data streams. A new data structure called SW.Tree is proposed, and a new algorithm minning frequent patterns from data streams is designed. This algorithm is applied to frequent pattern mining in network intrusion detection model, which achieves good results.