Application of Bayesian Optimization in Router Port Testing: An Improved Port Scanning Technique

This paper mainly explores the application of Bayesian optimization in router port testing, aiming to improve the efficiency and accuracy of port scanning by constructing a Bayesian optimization model. Since the existing port scanning methods have problems of low efficiency and accuracy, we seek to provide a superior solution through Bayesian optimization. In this process, we first introduce the basic principles of Bayesian optimization, then construct a Bayesian optimization model based on this theory, which takes scanning time and accuracy as optimization goals. In the experimental section, we conduct experiments on two public datasets to verify our method. The experimental results show that compared with traditional methods, the Bayesian optimization method can significantly improve the efficiency and accuracy of port scanning. Especially when the number of scans increases, the advantages of the Bayesian optimization method are more obvious. In general, Bayesian optimization provides a new and effective solution for router port testing and opens up new ideas for future research in the field of network security.