Abstract
In this work, a novel Adaptive Hybrid Immune Detector Maturation Algorithm is proposed for anomaly detection. T-detector Maturation Algorithm and Dynamic Negative Selection Algorithm are combined with a new state transformation model. Experiment results show that the proposed algorithm solves the population-adapt problem and can generate detectors with higher affinity.
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Chen, J., Chen, W., Liang, F. (2010). Adaptive Hybrid Immune Detector Maturation Algorithm. In: Corchado, E., Graña Romay, M., Manhaes Savio, A. (eds) Hybrid Artificial Intelligence Systems. HAIS 2010. Lecture Notes in Computer Science(), vol 6077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13803-4_25
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DOI: https://doi.org/10.1007/978-3-642-13803-4_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13802-7
Online ISBN: 978-3-642-13803-4
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