Relationship Between Artificial Intelligence and Machine Learning in Network Monitoring

Abstract

Artificial Intelligence and Machine Learning can have a close relationship. AI is a discipline that focuses on developing systems that can perform tasks that require human intelligence, where Machine Learning is one of the main branches of AI that deals with the development of algorithms and statistical models to analyze network data in real-time, identify patterns and behaviors and take appropriate actions, thereby strengthening the detection of security threats in the network through network traffic data analysis, ML algorithms can learn from normal traffic patterns and identify suspicious behavior in analyzing traffic data, ML algorithms can learn normal traffic patterns from users, devices, or applications. The anomaly detection method uses a different approach by training the model to recognize the usual patterns in the data and identifying data that differs from those patterns as anomalies. The purpose of this research is to improve security threat detection, analyze network performance efficiently, identify unusual behavior patterns and improve the effectiveness and efficiency of network monitoring with the results obtained are increased detection of security threats, more accurate identification of anomalies, recognition of new attack patterns, real-time network performance monitoring and reduction in the number of false positives.