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.
M. Ping, H. Zhengbing and Z. Ji, "A Novel Anomaly Detection Algorithm Based on Real-Valued Negative Selection System," International Workshop on Knowledge Discovery and Data Mining(WKDD), Adelaide, Australia, 2008, pp. 499-502.