在这篇论文,我们在场对基于网络的侵入察觉适用的一个适应异例察觉框架。我们的框架采用模糊的簇算法没有内在的数据的先验的知识,以一种联机、适应方式检测异例。我们由从 KDD CUP99 数据集合在网络记录上执行实验评估我们的方法。
In this paper, we present an adaptive anomaly detection framework that isapplicable to network-based intrusion detection. Our framework employs fuzzy cluster algorithm to detect anomalies in an online, adaptive fashion without a priori knowledge of the underlying data. We evaluate our method by performing experiments over network records from the KDD CUP99 data set.