Development Trend of Computer Network Security Technology Based on the Big Data Era

Abstract

With the rapid development of internet technology, big data technology (BDT) is becoming more and more mature in the development, and quickly showing its own innate advantages and acquired uses. Now the world generates a large amount of data every day, and these data are transformed the speed of information and knowledge that can be stored depends not only on the technology and management of the data, but also on the degree of network security. In many network security perception technologies, the main method is to determine network behavior and its potential impact by analyzing data entries on the network. However, in the case of big data, the existing network security state awareness model has disadvantages such as heavy resource burden, low accuracy of analysis results, low accuracy, and low processing efficiency, and cannot be applied to large-scale real-time scenarios. The method adopted in this paper is to first verify the smaller-scale data, thereby speeding up the process of model training and model parameter adjustment, and reducing the time spent on model feasibility verification. The experimental results surface: the data-trained model has reached a high level of accuracy in the data detection rate. The average detection rate is as high as 95%, This proves that network security urgently needs the help of big data analysis technology to make changes to meet the needs of development.