Sensor Network Security Risk Prediction and Control Method Based on Big Data Analysis

Abstract

The security prediction and control program of sensor network based on big data analysis is studied. First of all, in view of the shortcomings of existing security measures, this paper regards security standards as a challenge. Based on the changes of network security before and after the attack, the concept of “network security line” is proposed to select and simplify the security measures that can meet the needs and affect the real security and monitor the counting process of the network. Then, for counterattack, several models of topology security measurement based on stochastic process are developed to check the topology security. Finally, the experimental design of the risk assessment method is found by creating a risk receiving data model, deleting data features, and recreating distributed data. Experimental results show that the efficiency of this method is above 90% when the estimated distance is 10–40 m. The working power is 196∼461 Hz, lower than the normal standard. The time delay is less than 0.3 s, and the real-time performance is better than ordinary models. The relative error is less than 3%, and the accuracy is higher.