Negative selection algorithm based on immune suppression

The negative selection algorithm (NSA) is one of models in artificial immune systems. In this paper, two issues existed in traditional NSAs are described. Inspired by immune suppression mechanism, a novel framework of NSA that combining boundary selves and detectors to perform detection is proposed. By introducing the framework into V-detector algorithm, the improved algorithm is implemented and applied with synthetic data and real data. The experiment results show that the new algorithm based on immune suppression ensures better detection performance with fewer detectors.