一种基于异常的自适应非选择性算法研究

A self-adaptive negative selection approach for anomaly detection

本文研究的重点是检测器生成算法,在非选择性变异算法(NegativeSelectionMutation,NSMutation)的基础上,提出了一种自适应非选择性算法,完成了算法的设计、性能分析和实验。实验结果表明,新算法在正确检测、错误检测、计算时间上都表现出优越的性能。

Detector generating algorithms are the emphasis of this research. Based on Negative Selection Mutation algorithm, a new Self-Adaptive Selection algorithm is presented as detectors generating methods. Its design, performance, analysis and experiment is finished. The result of the experiments shows that the new algorithm outperforms the NSMutation in true detections, false detections and computation time.