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The computer network is prone to stop service and network crash under the intrusion of DDoS. In order to improve the network security, a DDoS attack detection method of computer network based on artificial bee colony algorithm is proposed. According to the correlation between feature samples, an adaptive intrusion detection information analysis model of computer network DDoS attack is constructed. According to the mapping relationship between network data stream and potential space, the features of DDoS attack data are extracted by combining the feature differences between test samples and learning samples. An intrusion detection data processing terminal is set up on the base station, and the artificial bee colony algorithm is used to optimize the individual optimal value and the global optimal value of computer network attack detection. According to the results of dynamic optimization and combinatorial optimization of artificial bee colony, the feature extraction and clustering analysis of attack information between combined network traffic data are realized, and the continuous multivariable optimization problem in the process of DDoS attack detection in computer network is solved. The simulation test results show that this method has better optimization ability, higher accuracy and efficiency than the traditional method.