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To study the characteristics and performance of the deep learning in intelligent intrusion detection, two hybrid algorithms, which combine restricted Boltzmann machine (RBM) with support vector machine (SVM) and deep belief network (DBN) respectively, are used to analyze the accuracy, false positive rate, false negative rate and testing time with the data set used for The Third International Knowledge...
Support vector machine-based intrusion detection methods are increasingly being researched because it can detect novel attacks. But solving a support vector machine problem is a typical quadratic optimization problem, which is influenced by the feature dimensions and number of training samples. Feature selection or attribution reduction can help reduce the SVM classification time and saving memory...
The support vector machines are a widely used tool for classification. In this paper, firstly the method of selected features of Windows registry access recorder to construct detection data set was discussed and two kinds of feature representation methods adapted to SVM algorithm were described. Secondly, the algorithms of standard SVM that are used to classification was presented. At last, we implemented...
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