Research on the Data Pre-Processing in the Network Abnormal Intrusion Detection

ABSTRACT

The data pre-processing is a very important step in network abnormal intrusion detection, and directly affects the accuracy of the subsequent detection. In this paper, there are two issues in the network abnormal intrusion detection based on the hierarchical clustering so that some improvements should be made in the data pre-processing stage: first, there is the redundancy and attribute weight problem, each attribute with the weights should be attributing reduced with the use of rough set theory. Second, Aiming to the problem of the continuous data discretization in the rough set theory, an adaptive discrete algorithm for the data characteristics is proposed, and the algorithm determines the intervals of the discretization on the basis of the distribution of the sample attribute values. At last, the two improved methods are experimented and compared with the use of the existing discretization method. The experimental results demonstrate the effectiveness and accuracy of the algorithm.

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