Detecting Communication Network Anomalies and Intrusions
G. Shanmugavadivel, S. Gopinath, K. Gowtham, M. Mugesh · 2022 6th International Conference on Intelligent Computing and Control Systems (ICICCS) · 2022
In cyber security, a significant research effort has been dedicated to identifying network infrastructure abnormalities & incursions. This research work utilizes the supervised machine learning techniques such as Support vector Machine (SVM) and Broad Learning System (BLS) to detect the anomalies and incursions in the packet data network with provided input database. To train and test the developed models, information from the Internet’s routing tables, computer-generated network of military sites, and an experimental testbed are employed. These datasets provide information on both incursions and normal traffic. Finally, the proposed research study compares two different machine learning algorithms based on reliability, F-score, and training time.