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An Improved Evolution Algorithm of Immune Detectors for Network Data Analysis

机译:网络数据分析的免疫检测器改进的演化算法

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Traditional immune algorithms use binary strings to represent detectors and adopt r-contiguous matching algorithm to match detectors. It reduces the accuracy of network data analysis. In order to raise the above performance of network data analysis based on immune algorithms, an improved evolution algorithm of immune detectors for network data analysis is proposed in this paper. Traditional creation method, traditional dynamic evolution method and traditional matching method are analyzed. Network data are simulated with network packets. Immune detectors are simulated. Computation algorithm of similarity is set up. Generation algorithm of immune detector is designed. Based on the above simulation and sub algorithms, the total network data analysis algorithm is constructed. A prototype software is developed to verify the effectiveness of the proposed algorithm. The experiment results show that the proposed immune algorithm has better performance.
机译:传统免疫算法使用二进制字符串来表示探测器并采用R连续匹配算法匹配探测器。 它降低了网络数据分析的准确性。 为了提高基于免疫算法的网络数据分析的上述性能,本文提出了一种用于网络数据分析的免疫检测器的改进演化算法。 分析了传统的创建方法,传统的动态演化方法和传统匹配方法。 使用网络数据包模拟网络数据。 模拟免疫检测器。 设置了相似性的计算算法。 设计了免疫检测器的生成算法。 基于上述仿真和子算法,构建了总网络数据分析算法。 开发了一种原型软件以验证所提出的算法的有效性。 实验结果表明,所提出的免疫算法具有更好的性能。

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