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Most of current intrusion detection systems are based on machine learning methods but very few till now use clustering algorithms as a preprocessing layer to reduce the high dimensionality of data, which is difficult to analyze. In this paper, the authors introduce Modular Neural Network for intrusion detection, which apply Principal Component Analysis (PCA) as preprocessing layer for reducing huge information quantity presented in Knowledge Discovery and Data Mining (KDD99) data set. PCA significantly reduce the high dimensionality of data set without loss of information.
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