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Multiclass genetic programming based approach for classification of intrusions

机译:基于多类遗传规划的入侵分类方法

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Classification plays a major role in distinguishing the normal traffic from the intrusive ones in any intrusion detection system. Different approaches have been used by various researchers to improve the accuracy of the classifiers for binary and multiclass classification problems. Genetic programming (GP) algorithms have been applied in the previous studies and have confirmed that it performs well for classification problems. In our work, we have used a variation of the mutation operation which will be applied when the fitness of the individual does not change significantly for a specified number of generations. Several experiments were conducted using the standard GP method and using the modified mutation operation and the results obtained show that our approach gives good results for multiclass problem in comparison to the standard GP method.
机译:分类在区分任何入侵检测系统中的正常流量和入侵流量方面起着主要作用。各种研究人员已使用不同的方法来提高针对二元和多分类问题的分类器的准确性。遗传编程(GP)算法已在先前的研究中应用,并已证实它在分类问题上表现良好。在我们的工作中,我们使用了变异操作的变体,当个体的适应度在指定的世代数中没有显着变化时,将应用该变体。使用标准GP方法和修改后的变异操作进行了几次实验,获得的结果表明,与标准GP方法相比,我们的方法对于多类问题给出了良好的结果。

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