Relationship Between Artificial Intelligence and Machine Learningin 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