基于多目标进化算法的入侵检测特征选择

Feature selection based on multi-objective evolutionary algorithm for intrusion detection

针对入侵检测系统要求检测率和误报率均衡优化,提出一种由顺序搜索策略改进的多目标进化算法,对特征空间进行压缩,以选择最优特征子集。实验结果表明,改进的多目标进化算法实现了检测率与误报率的均衡优化,较好地提高了入侵检测系统的性能。

According to that an intrusion detection system needs to achieve the best trade-off between detection rate and false positive rate,an improved multi-objective evolutionary algorithm is proposed to reduce the feature space and then select the best feature subset.The experiment results show that the best trade-off between detection rate and false positive rate can be achieved by the improved multi-objective evolutionary algorithm.The algorithm can improve the performance of the intrusion detection system.