Decision Tree Based Approach Intrusion Detection for Predefined Features Using Fuzzy Class Association Rule Mining

Provided by: International Journal of Engineering Associates
Topic: Security
Format: PDF
As the Internet services and its importance expand, intrusion detection technique is the most important t o find and detects novel or unknown attacks. In this paper network intrusions are detected to provide good performance using decision tree based approach by combing fuzzy class association rule mining. Extraction of class Association rules are done from the database thus enhancing the detection ability. Both the discrete are continuous attributes are present in the database. To show that this method provides high detection rate KDD cup database are to be used for experimental results. A comparative analysis is also done using Machine Learning Techniques called SVM (Support Vector Machine) to show an efficient detection rate.

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