Network Traffic Analysis Using Machine Learning

Abstract

Network traffic analysis and prediction has applications in a variety of fields and has recently attracted a considerable number of studies. To find numerous issues with current computer network applications, various sorts of studies are carried out and reported. A proactive strategy to guarantee safe, dependable, and high-quality network communications is network traffic analysis and prediction. For network traffic analysis, several methods, including data mining and neural network-based methods, are developed and evaluated. For the prediction of network traffic, numerous linear and nonlinear models have been suggested. A wide range of exciting combinations of network analysis and prediction approaches are used to produce effective and successful results. An overview of several network analysis and traffic prediction approaches is provided in this study. The uniqueness and rules of the previous studies are examined. In addition, various areas of network traffic analysis and prediction that have been carried out are summarized.