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Method of network traffic classification using Naïve Bayes based on FPGA

机译:基于FPGA的朴素贝叶斯网络流量分类方法

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In order to solve the problems in High-speed network that the general software methods of traffic classification cannot meet the requirements of real-time; a method of Naïve Bayes based on FPGA for network traffic classification was proposed. This method is using Naïve Bayes based on FPGA for the network traffic classification, whose classification decisions can be reconfigured on the basis of classification results and network environment. In this way, the classification accuracy is guaranteed. And besides, FPGA-based Naïve Bayes, because of the hardware acceleration, is more rapid than Naïve Bayes based on software. Simulation results show that the former is 443 times than the latter in the classification rate. It can be inferred that this method is effectively for classification of High-speed network traffic.
机译:为了解决高速网络中一般的流量分类软件方法不能满足实时性的问题;提出了一种基于FPGA的朴素贝叶斯网络流量分类方法。该方法使用基于FPGA的朴素贝叶斯进行网络流量分类,其分类决策可以根据分类结果和网络环境进行重新配置。这样,保证了分类精度。此外,基于FPGA的NaïveBayes,由于硬件加速,比基于软件的NaïveBayes更快。仿真结果表明,前者的分类率是后者的443倍。可以推断,该方法对于高速网络流量的分类有效。

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