DocumentCode :
1752978
Title :
Unified Negative Selection Algorithm for Anomaly Detection
Author :
Bai, Meng ; Zhao, Xiaoguang ; Hou, Zeng-Guang ; Tan, Min
Author_Institution :
Lab. of Complex Syst. & Intelligence Sci., Chinese Acad. of Sci., Beijing
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
4254
Lastpage :
4258
Abstract :
A novel negative selection algorithm is presented, which is inspired by the negative selection mechanism of the immune system that can detect foreign patterns in the complement (nonself) space. In the algorithm, the pattern space is unified into a certain interval and the foreign pattern detectors (in the complement space) are defined in the form of short intervals. Algorithm analysis reveals the bound of probability that detectors fail to detect an abnormal pattern and the bound of interval radius chosen to create a pattern interval. Experimental results show that the algorithm can generate detectors quickly and detect abnormal patterns effectively. These results also demonstrate the influence on algorithm performance when different pattern interval radii are chosen
Keywords :
genetic algorithms; pattern recognition; abnormal detection; anomaly detection; foreign pattern detection; immune system; unified negative selection; Algorithm design and analysis; Automation; Detectors; Failure analysis; Immune system; Intelligent control; Intelligent systems; Laboratories; Pattern analysis; abnormal detection; immune system; negative selection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1713177
Filename :
1713177
Link To Document :
بازگشت