A Trigonometric Function-Based Big Data Model for Network Information Security Control Mechanisms

Abstract

The study of trigonometric relationships is a result of a combination of mathematics and engineering techniques. It plays an important role in computer network systems, and its applications are involved in all aspects of computer network systems, which mainly include data storage, information retrieval, and retrieval. Big data technology can analyze and integrate massive and complex information, make effective use of data, and provide an important basis for computer network security control. At present, traditional encryption algorithms mainly deal with information data through the use of cryptographic theory, but with the progress of the times, there are higher requirements for the security of data for transmission. For instance, cryptography proposes the principle of confidentiality and uses key generation, plain text flow processes, and encryption algorithms to control the flow of ciphertext, all of which require extensive research on network system security. In this paper, we will study the network security control method of a big data model of triangular fuzzy quotient function relationships and build a targeted and widely applicable computer network system security mat system with high practical value. According to the proposed model, it has the highest accuracy at 94.5%, precision at 93.6%, and recall at 93.8. The results obtained demonstrate a noteworthy enhancement in performance when compared to the current techniques.