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- W2394045144 abstract "Aimed at the redundant features in intrusion detection data and redundant instances in intrusion detection system,a bidirectional data reduction method based on the principal component analysis(PCA) and combined steady-state genetic algorithm is proposed.Firstly,PCA is employed to reduce the features and the redundant features are removed effectively.Then the combined steady-state genetic algorithm is used to reduce the number of instances.A model of intrusion detection system based on neural networks is presented.The model characterizes itself in muticlassifications and easy updating for the adaptation to new intrusion modes.Experiments on KDD CUP'99 validate the effectiveness of this method.It is indicated that the proposed bidirectional data reduction method can be used to deal with the reduction of big data set." @default.
- W2394045144 created "2016-06-24" @default.
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- W2394045144 date "2009-01-01" @default.
- W2394045144 modified "2023-10-16" @default.
- W2394045144 title "Bidirectional data reduction based on PCA and combined SSGA in intrusion detection system" @default.
- W2394045144 hasPublicationYear "2009" @default.
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