Dynamic Adjustment of the TLS Protocol Based on Naive Bayes

The adaptive adjustment of the TLS (Transport Layer Security) protocol aims to address various security threats and performance requirements in the current network environment. It is crucial for the reliability of online transactions and data transmissions. This research will adopt a comprehensive research approach, integrating network traffic analysis, naïve bayes machine learning algorithms and simulation experiments. It is expected to develop a mechanism that can dynamically adjust the cipher suite parameters of the TLS protocol according to the real-time network situation, so as to strengthen the security of data transmission and improve the efficiency of network communications.