Research on computer database intrusion detection based on clustering algorithm
Lu Zhang · 2023
This paper combines the idea of decision tree classification and ant colony clustering, and proposes a multilevel hybrid classifier combining decision tree and ant colony algorithms, i.e., a tree classifier improved by Algorithm C4.5 and a method combining two techniques of applying ant colony clustering algorithms to hybrid data to distinguish which are normal intrusions, and the attack data types are layered, with the first layer being normal data, the second layer being other data and the third layer is special data. Experiments show that this new method is very effective in intrusion detection, it has a very low false alarm rate, while maintaining a relatively acceptable false alarm rate, and can also be appropriate to detect unknown intrusion detection thus improving the intrusion detection rate.