Computer Network Information Security Threat Identification Technology Based on Big Data Clustering Algorithm

Due to the vulnerability of the structure and characteristics of the computer network information system itself, there will be many inevitable network information security problems. In order to solve the shortcomings of the existing research on computer network information security threat identification technology, based on the discussion of big data clustering algorithm and computer network information security, this paper briefly introduces the configuration of the data set and experimental environment. And discuss the workflow design of the designed model architecture, and finally analyze the application of the designed identification technology framework. The experimental data show that the accuracy rate of the computer network information security threat identification technology of the big data clustering algorithm proposed in this paper is as high as 91.5%, the recall rate is as high as 91.4%, and the detection rate is as high as 86.4%. Therefore, the applicability of the information security threat identification technology based on the big data clustering algorithm can be seen.