Abstract An adaptive immune wavelet network based intrusion detection model and the related algorithm are proposed by combining an adaptive wavelet network model with immune algorithm in this paper. The model not only avoids blindness of determing parameters and construction of neural network, but also alleviates sensitivity to initialization. The experimental results show detection rate acquired in this algorithm is higher than that in other algorithms and its convergency speed is higher than others’. Moreover, the relationship between False Negatives and False Positives can be restricted and balanced by adjusting a threshold value.
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