Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavior. With new types of attacks appearing continually, developing flexible and adaptive security-oriented approaches is a severe challenge. Network intrusion detection has become increasingly important with the rapid rise of internet technology and the accompanying growth in the number of network attacks. Our goal is to create an anomaly detection model to detect a cyberattack based on the UNSW-NB 15 dataset. The objectives of this analysis are Create an anomaly detection model to detect a cyberattack based on the UNSW-NB 15 dataset. Our Specific objectives are: To understand the criteria for an anomaly. To give insights into the frequency & types of attacks. To provide recommendations for deployment.