Computer Network Information Security Protection Based on Big Data Clustering Algorithm

With the rapid growth of social economy and the improvement of living standard, the network information platform emerges as the times require, which provides convenient conditions for people to communicate and interact efficiently. Driven by big data, computer network security becomes more critical and important, which can ensure the safety of people and property. Driven by big data, the problem of computer information security has become more serious. We need to be alert to the influences from many aspects, and we need to discuss the protection strategies from many aspects. In this paper, driven by big data, the computer information security and protection are studied, and a computer network information encryption algorithm based on fuzzy clustering algorithm (FCM) is proposed, which provides ideas for the theoretical strategy of maintaining network security. The simulation results show that after many iterations, the error of this method is obviously better than that of the comparison algorithm in psychological crisis analysis, with the error reduced by 35.24% and the recall rate reaching 95.69%, which is 15.33% higher than that of the comparison algorithm. This method can reduce the problem of data theft and loss, ensure the safe operation and use of various data, solve the cross-linking relationship, and provide corresponding theoretical support for computer information security protection.