A New Network Traffic Classification Method Based on Classifier Integration

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Provided by: Science & Engineering Research Support soCiety (SERSC)
Topic: Security
Format: PDF
With development of scale, diversity and complexity of network traffic, the drawbacks of traditional machine learning methods on traffic classification is gradually exposed, especially the false positive problem in large-scale real network traffic classification is particularly serious. In this paper, aiming at reducing the false positive rate of network traffic classification, an effective network traffic classification method - CMM method. CMM method contains three steps, including dividing the training set into clusters, forming sub-classifiers and classifier integration in accordance with the principle of minimization and maximization.
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