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- W2024914097 abstract "The paper presents an approach based on principles of immune systems to the anomaly detection problem. Flexibility and efficiency of the anomaly detection system are achieved by building a model of network behavior based on the self-nonself space paradigm. Covering both self and nonself spaces by hyperrectangular structures is proposed. Structures corresponding to self-space are built using a training set from this space. Hyperrectangular detectors covering nonself space are created using niching genetic algorithm. A coevolutionary algorithm is proposed to enhance this process. Results of experiments show a high quality of intrusion detection, which outperform the quality of recently proposed approach based on hypersphere representation of self-space." @default.
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- W2024914097 date "2006-07-08" @default.
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- W2024914097 title "Immune anomaly detection enhanced with evolutionary paradigms" @default.
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- W2024914097 doi "https://doi.org/10.1145/1143997.1144018" @default.
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