›› 2012, Vol. 42 ›› Issue (05): 1251-1256.

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Optimization algorithm for immune real-value detector generation

CHAI Zheng-yi1,2, WU Hui-xin3, WU-Yong1   

  1. 1. School of Information Science and Engineering, Hennan University of Technology, Zhengzhou 450001,China;
    2. School of Computer Science and Technology, Xidian University, Xi'an 710071, China;
    3. Department of Information Engineering, North China University of Water Conservancy & Electric Power, Zhengzhou 450001,China
  • Received:2011-04-20 Online:2012-09-01 Published:2012-09-01

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Abstract: A new optimized detector generation algorithm is proposed to overcome the shortcomings of available real-value variable-radius detector generation algorithms. By statistic analysis of the detector generation, a hypothesis testing based detector generation process is proposed. The result of the hypothesis testing is taken as one of the control parameters to end the algorithm, thus, it can effectively avoid the generation of redundant detectors. Meanwhile, the algorithm makes full use of the distribution of self-space, optimizes the center position and expands the radius of the detectors in order to generate the detector with large coverage. The 2DSyntheticData, the actual Irish data set and biomedical data set are used to test the algorithm. Experiment results show that the algorithm performs very well that it improves the detection rate, reduces the number of required detectors.

Key words: computer systems organization, hypothesis testing, negative selection algorithm, detector, anomaly detection, detection performance

CLC Number: 

  • TP18
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