Research on Campus Network Security Management Technology Based on Big Data

Abstract

This paper improves the security management and control ability of campus network management, studies the security management control model of campus network management, and puts forward a security evaluation and evading model of campus network management based on big data. The management security data mining is carried out by using the statistical analysis method of campus network transmission traffic, and the constraint distribution model of campus network management security control is constructed. Big data fusion and association rule mining methods are used to evaluate the security of campus network management quantitatively, and the data of campus network management security evaluation are tested by grouping regression, and the correlation dimension characteristic quantity of traffic transmission sequence of campus network management is extracted. This paper analyzes the cross-correlation characteristic quantity of the output traffic of campus network management and evaluates the network security according to the anomaly of the characteristic to realize the optimization control of campus network security management. The simulation results show that the traffic anomaly prediction ability is higher and the network intrusion detection ability is stronger by using this method in campus network security management.