Network Traffic Intrusion Detection

The paper explores the application of machine learning algorithms for network traffic intrusion detection with the aim of enhancing the security of information systems. More specifically, it provides a comprehensive insight into the current state of the art in intrusion detection, and gives a review of relevant literature, research methodology, implementation of various machine learning models, and analysis of the obtained results. Our findings indicate the outstanding potential of models, such as decision trees, in identifying malicious activities, offering valuable guidance for the development of more efficient systems for network security.