Decision Tree Based IDS Implementation: Review
Network security technology has become crucial in protecting government and industry computing infrastructure. Modern intrusion detection applications face complex requirements - they need to be reliable, extensible, easy to manage, and have low maintenance cost. In recent years, data mining - based Intrusion Detection Systems (IDSs) have demonstrated high accuracy, good generalization to novel types of intrusion, and robust behavior in a changing environment. Still, significant challenges exist in design and implementation of production quality IDSs. This paper, proposes a system, named "Decision tree based IDS implementation: review", which will capture live process and will compare with the authors' training data sets to find out normal and abnormal behavior of the process, the data mining algorithm which they are using is more efficient.