Botnets employ Domain Generation Algorithms(DGA)to generate numerous random domain names to evade detection by the security defense system.In order to solve the problems of low accuracy and limited generalization capabilities,this article proposes attentional feature fusion network.This model combines an input layer,an Embedding layer,a Convolutional Neural Network layer,an attention module,and a Long Short-Term Memory layer,achieving hierarchical feature extraction and substan-tially improving model's performance.Experimental results indicate that the approach exhibits significant improvements in various indicators,showcasing outstanding DGA malicious domain name detection capabilities.
维普
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