A niching negative selective genetic algorithm for self-nonself discrimination in a computer

Presents a niching negative selective genetic algorithm for self-nonself discrimination in a computer. From the view point of biological immune principles, the advantages and existing problems of the negative selection algorithm as a distributed anomaly detection approach are introduced. The problem of compounding negative selection with a genetic algorithm is discussed. Experiments report that the algorithm proposed shows diversity, less time of generating detectors and efficiency.