Title :
An improved V-detector algorithm of identifying boundary self
Author :
Gui-Yang Li ; Li, Hai-bo ; Zeng, Jie ; Hai-Bo Li
Author_Institution :
Sch. of Comput. Sci., Sichuan Univ., Chengdu, China
Abstract :
The V-detector algorithm is a real-valued negative selection algorithm with variable-sized detectors. In this paper, several flaws existed in the algorithm are investigated and analyzed. An improved V-detector algorithm is also proposed and implemented. The improved algorithm divides the collection of self samples into boundary selves and non-boundary selves. The identifying and recording mechanism of boundary self are introduced during the generation of detectors. The experiment results showed that the new algorithm covers the holes existed in boundary between self region and non-self region more effectively than traditional negative selection algorithm does. In the meantime, the new algorithm can reduce the number of detectors under the circumstance of ensuring detection performance.
Keywords :
artificial immune systems; heuristic programming; statistical analysis; identifying boundary self; improved V-detector algorithm; real-valued negative selection algorithm; Algorithm design and analysis; Biological system modeling; Computer science; Cybernetics; Detectors; Fault detection; Immune system; Intrusion detection; Machine learning; Machine learning algorithms; Boundary self; Hypothesis testing; Negative selection algorithm; V-detector;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Hebei
Print_ISBN :
978-1-4244-3702-3
DOI :
10.1109/ICMLC.2009.5212774