Abstract: In the network environment of big data,the method of detecting the abnormal behavior of the traditional user have the question that it can not meet the massive data detection requirements,can not respond to the constantly updated abnormal behavior and malware quickly and does not consider the user behavior management and other issues,so that the accuracy and stability of the abnormal detection is insufficient.Combining the technology of network traffic analysis,this paper proposed a custom model of the abnormal user behavior detection based on deep neural network,which realizes fine-grained analysis of network traffic and customizes user behavior management settings to make user anomaly detection more closely integrated with the needs of specific network environments.The data of network traffic analysis was used as the input vector of the deep neural network algorithm to realize massive data detection and custom user behavior management,and detect unknown abnormal behavior.The experimental results show that the proposed method has high accuracy and robustness,can effectively implement custom user behavior management,and solve the shortage of the traditional user anomalies.

Key words: Custom, Deep neural network, Network traffic, User anomalous behavior