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Aiming at the problems of low data processing efficiency and large error of traditional intelligent network security attack detection platform, this paper proposes a new solution. In this scheme, the data extraction model and big data analysis are used to build an intelligent network security attack detection platform. The network security inspection data extraction model is constructed by combining feature template, convolution neural network algorithm model and conditional random field algorithm to extract network security detection data. Among them, the local feature vector is extracted by feature template, and the initial local vector sequence is obtained by sentence conversion. Each network security monitoring data sample is convoluted and aggregated by CNN algorithm, and its feature information is extracted. The semantic feature and local feature are combined, and the sequence is marked by conditional random field algorithm,