Technology Analysis of Network Anomalous Behavior Detection Based on Machine Learning
Shuguang Wu, Hongyan Wang, Yu Wang, Nanjiang Yan · 2022 3rd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE) · 2022
In the increasingly changing network environment, network anomalous behaviors show a trend of concealment and complexity, and it is crucial to detect anomalous behaviors and eliminate hidden dangers to enhance network system security. Researchers have applied machine learning methods to anomaly detection and achieved good results. This paper presents a review of these studies. First, the concept of anomalous behavior, its sources and its analysis methods are introduced, and then an overview of the application of machine learning methods is given, detailing in order the commonly used datasets, data pre-processing methods and the application of machine learning in anomaly detection. Finally, the advantages and disadvantages of different methods are summarized, and the main challenges and solution ideas faced in the current anomaly detection tasks are analyzed.