International Workshop on Knowledge Discovery and Data Mining (2008)
Jan. 23, 2008 to Jan. 24, 2008
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WKDD.2008.110
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.
Ma Ping, Hu Zhengbing, Zhou Ji, "A Novel Anomaly Detection Algorithm Based on Real-Valued Negative Selection System", International Workshop on Knowledge Discovery and Data Mining, vol. 00, no. , pp. 499-502, 2008, doi:10.1109/WKDD.2008.110