Machine Learning Techniques for Anomaly Detection in Network Traffic
Richa Singh, Nidhi Srivastava, Ashwani Kumar
Abstract
In today's technological era, anomaly detection is a major concern in front of network users. Due to the development of various network techniques, network users are also increased which leads to more traffic on the network, and due to this, it's very difficult to recognize the anomalous patterns. This paper discussed the overview of various ML techniques used to solve the problem of anomaly detection along with their pros and cons and also discussed here the framework/model’s accuracy level. In this survey, strategies for identifying and mitigating abnormalities in network traffic are discussed and compared the result in terms of its accuracy and anomaly types. The current research gaps and important research concerns in network traffic anomaly detection are presented in detail. We hope that the analysis, comparisons, and after that, the identification of gaps will point out the researchers in the right direction for doing advanced development in this field.