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滑动窗口数据流聚类算法在IDS中的应用
引用本文:朱 琳,朱参世. 滑动窗口数据流聚类算法在IDS中的应用[J]. 计算机工程与应用, 2014, 50(1): 87-90
作者姓名:朱 琳  朱参世
作者单位:空军工程大学 工程学院,西安 710038
摘    要:针对传统入侵检测系统难于适应日益增长数据量对实时处理能力的需求问题,运用滑动窗口、数据流聚类技术,设计了基于滑动窗口数据流聚类算法,并构建了基于该算法的IDS网络安全防御模型。通过对该模型仿真验证,证明该网络安全防御模型能较好地适应高速网络的入侵检测需求。

关 键 词:数据流  挖掘算法  入侵检测  网络安全  

Data stream sliding window clustering algorithm applied in IDS
ZHU Lin,ZHU Canshi. Data stream sliding window clustering algorithm applied in IDS[J]. Computer Engineering and Applications, 2014, 50(1): 87-90
Authors:ZHU Lin  ZHU Canshi
Affiliation:Engineering College, Air Force University of Engineering, Xi’an 710038, China
Abstract:Aimming at the traditional intrusion detection system is difficult to adapt to the increasing amount of data demand for real-time processing capability, this paper uses of sliding window and the data stream clustering technology to design a clustering algorithm based on sliding window data streams, and build the IDS network security defense model based on the algorithm. The validation of model simulation proves that the network security defense model is able to adapt to the high-speed network intrusion detection requirements.
Keywords:data streams  mining algorithms  intrusion detection  network security
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