Intelligent Intrusion Detection System using Decision Tree Classifier and Bootstrap Aggregation

This paper proposes a novel methodology in the area of threat intelligence by combining statistical analysis with Intrusion Detection System. The preferred threat intelligence model identifies potential malicious connections for a single node computer system utilising the IP addresses of the devices that are connected to the system. It can be inferred from the results that the proposed system performs better in terms of accuracy, True Positive Rate and False Positive Rate.