원문정보
초록
영어
In the modern age of information technology security of valuable asset become much important issue. Intrusion detection system plays a most important role in this area. It protects the system by attacks or threats by unauthorized access or person. The previous study has identified the need for more enhancements in the research of intrusion detection. This study gives the outline for intrusion detection and proposed a hybrid classification based method based on Decision Tree and K-Nearest Neighbor. This experiment perform on the bases of cross-10 fold validation techniques on the basis of decision tree and KNN classifiers and proposed hybrid classifier by using KDD cup dataset. Experimental result shows that the proposed idea gives good result as compared to individual base algorithms
목차
1. Introduction
2. Literature Review
3. Dataset Description
3.1. Corrected KDD Dataset
3.2. 10% KDD Dataset
4. Decision Tree and K-Nearest Neighbor
5. Ensemble Mathods
6. Proposed Hybrid Algorithm
5. Conclusion and Future Works
References