Internet technologies are now utilized in almost every domain to gather data streams and also to monitor important events in an organization. However, these data streams are affected by abnormal or unusual pattern widely known as anomalies, which is responsible for malicious attacks, hardware failure, software failure, and reading errors. Hence, a dynamic, effective anomaly detection model is established in this research to enhance the quality of data gathered by the networks. The deep belief neural network is employed to obtain promising results in anomaly detection. The classifier performanc...