A Novel Anomaly Detection Algorithm Based on Real-Valued Negative Selection System

In this paper, a new method of detector generation and matching mechanism for negative selection algorithm(NSA )is introduced with variable properties, which are called the Nsa-Vs-Detector. The detectors can be variable in different ways using this concept, the paper describes an algorithm when the variable parameter is the size of the detectors in real-valued space. The algorithm is tested with a synthetic datasets, the new method improves the NSA ´s efficiency and reliability without significant increase in complexity.