Evaluation Of Efficiency For Intrusion Detection System Using Gini Index C5 Algorithm
S. Devaraju
Dr. S. Devaraju, Department of Computer Science and Applications, Sri Krishna Arts and Science College, Coimbatore-8, Tamil Nadu, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 2196-2200 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8593088619/2019©BEIESP | DOI: 10.35940/ijeat.F8593.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Security is the critical part in the computers and the networks which connect the computers each other’s through network for communication or exchange the data. It is a wide complex to secure the data while transmitting the data between the system/networks. The intrusion detection is a mechanism to protect the data. There are various existing mechanisms for intrusion detection namely neural network, data mining technique, fuzzy logic, statistical technique etc. In this paper, Principal Component Analysis is applied to reduce the features and Gini index C5 algorithm is used to investigate and evaluate the efficiency and false positive rate. The benchmark KDD dataset is used to evaluate the efficiency and minimize the false positive rate using Gini index C5 algorithm and compare with other algorithm which shows significant improvement and to experiment the KDD Dataset to improve the efficiency and minimize the false positive rate using MATLAB software and demonstrated with the KDD dataset.
Keywords: Intrusion Detection, Gini Index C5, KDD Cup, MATLAB