Application of Data Mining Technology in Computer Network Virus Prevention

With the continuous advancement of Internet technology, computer network viruses have become a ubiquitous threat and have a certain impact on people's daily lives. Therefore, research on how to effectively prevent and control computer network security attacks has become very important. This article aims to analyze the existing practical application experience of domestic and foreign scholars, explore the application of data mining technology(DMT) in the field of computer network security, and perform a performance test on the computer network virus prevention model. The test results show that the computer network virus interception rate is above 93%, the data throughput is 6783k-9347k, and the virus processing time is 11s-17s. This article puts forward a perspective on data mining and its utilization strategies to achieve the goals of better maintaining system stability and reducing economic losses, discusses methods of information classification and feature extraction, and introduces their applications in other fields and their future prospects. In the current environment, it is of great significance to apply DMT to the field of computer network security, because it can mine valuable information from massive network data, help understand the nature of network security issues, and provide support for data-based decision-making.