Evaluation of Information Security through Networks traffic traces for machine learning classification

Abstract

The classification's traffic is regarded as a significant study domain because to the rising demand among network users. In addition to improving the identification of network services and addressing difficulties related to the security of traffic networks, it also simplifies and improves the accuracy of a broad variety of Internet application modes and activities. Over the course of the last several years, a multitude of traffic classification algorithms have been developed alongside their effective implementation. This paper proposed evaluate the classification issues of information security which happened through networks traffic by using machine learning (ML) classification algorithm the RamdomForst by using NSL- KDD test and NSL-KDD train dataset to show the performance of testing data and training data.