The T-Detectors Maturation Algorithm Based on Genetic Algorithm

摘要

Negative selection algorithm is used to generate detector for change detection, anomaly detection. But it can not be adapted to the change of self data because the match threshold must be set at first. In this paper, inspired from T-cells maturation, a novel algorithm composed of positive and negative selection is proposed to generate T-detector. Genetic algorithm is used to evolve the detectors with lower match threshold. The proposed algorithm is tested by simulation experiment for anomaly detection and compared with negative selection algorithm. The results show that the proposed algorithm is more effective than negative selection algorithm. Match threshold is self-adapted and False Positive is controlled by parameter S.