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In order to share the knowledge of intrusion among distributed hosts and make the intrusion detect packages more efficient and reliable, a framework of distributed incremental intrusion detection based on SVM is proposed in the study. In this framework, the locate SVM detects the local attacks and take charge of collecting the new typical samples. A center SVM summarizes the distributed samples and...
Proposed a method of detecting intrusion using incremental SVM based on key feature selection. A center SVM summarizes the distributed samples and incorporates them to build the incremental SVM for locals. By eliminating the redulldant features of sample dataset the space dimension of the sample data is reduced. Using this method it can overcome the shortages of SVM-time-consuming of training and...
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