Application of combined kernel function artificial intelligence algorithm in mobile communication network security authentication mechanism

摘要

Security threats, security requirements, and adopted security policies in the new mobile environment have changed. As a key issue in the development of mobile communication, the mobile communication network security authentication mechanism has attracted the attention of academic circles and industry, and research on its security has become a research hotspot. Firstly, aiming at the security threats and security requirements in the heterogeneous mobile communication network environment, the architecture of the security authentication mechanism in this mobile environment is proposed. The security architecture consists of three layers (transport layer, service layer, application layer) and four domains (user domain, access domain, network domain, and application domain), and defined security features. The security architecture includes functional entities such as public key infrastructure and application servers and defines new security features for security threats in the application domain and user domain, so that the security architecture can meet the heterogeneous mobile communication network environment. Security needs. Secondly, a linear combination kernel function is used to construct a new class of kernel functions with different characteristics in a linear combination and satisfy the Mercer theorem. The combined kernel function has both global kernel function and local kernel. The advantages function and their weight on the combined kernel function can be adjusted by the weight coefficient factor, and a better comprehensive prediction effect is obtained in the support vector machine model. Finally, the experimental results also show that the support vector regression machine model based on combined kernel function can achieve higher learning precision.