The week's pick
Reseach Article
An Improved Intrusion System Design using Hybrid Classification Technique
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 117 - Number 10 |
| Year of Publication: 2015 |
| Authors: Rita Mandal, Shweta Yadav |
10.5120/20589-3028
|
Rita Mandal, Shweta Yadav . An Improved Intrusion System Design using Hybrid Classification Technique. International Journal of Computer Applications. 117, 10 ( May 2015), 20-23. DOI=10.5120/20589-3028
Abstract
The data mining is an essential tool for current age technology. It is very useful for various applications such as business intelligence, computational cloud and other research and science based projects. In this presented paper a new kind of intrusion system design is proposed and their implementation is presented using MATLAB. The proposed attack classification technique is based on the C4. 5 decision tree and the supervised back propagation neural network. During the attack classification the proposed system first pre-processes the input dataset. Therefore, in order to reduce the dimensions of the dataset, the KPCA algorithm is applied and then the C4. 5 data model is implemented for extracting the classification rules form the C4. 5 classifier. These rules are in the form of IF THEN ELSE format. Now the defined rules are processed by the using the back propagation neural network. The proposed model is tested on the different size of KDD cup dataset and the performance is provided. According to the obtained results the proposed data model provides the improved classification rates.
References
- Mala Bharti Lodhi, Prof. Vineet Richhariya, Prof. Mahesh Parmar, "An Implementation of IDS in a Hybird Approach And KDDCUP Dataset", International Journal ofResearch –Granthalayah, Vol. 2(Iss. 3):December,2014
- Mala Bharti Lodhi, Vineet Richhariya and Mahesh Parmar, "A survey on Data Mining based Intrusion Detection Systems", International Journal of Computer Networks and Communications Security,VOL. 2, NO. 12, DECEMBER 2014, 485–490
- Mahbod Tavallaee, Ebrahim Bagheri, Wei Lu, and Ali A. Ghorbani, "A Detailed Analysis of the KDD CUP 99 Data Set", proceeding of the 2009 IEEE symposium on computational intelligence
- Mradul Dhakar and Akhilesh Tiwari, "A Novel Data Mining based Hybrid Intrusion Detection Framework", A Novel Data Mining based Hybrid Intrusion Detection Framework, Vol. 9, No. 1, 2014, pp. 037-048
- Long-Sheng Chen, Jhih-Siang Syu, "Feature Extraction based Approaches forImproving the Performance of Intrusion Detection Systems", Proceedings of the International Multi Conference of Engineers and Computer Scientists 2015 Vol I,IMECS 2015, March 18 - 20, 2015, Hong Kong
- Kundan Kumar Mishra, Rahul Kaul, "Audit Trail Based on Process Mining and Log", International Journal of Recent Development in Engineering and Technology, Volume 1, Issue 1, Oct 2013
- AnkitaAgrawal, "Host Load Prediction in Computational Grid Environment", International Journal of Computer Applications (0975 – 8887) Volume 77– No. 10, September 2013
Index Terms
Keywords