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A Naive Gain Approach to Intrusion Detection Systems
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 70 - Number 23 |
| Year of Publication: 2013 |
| Authors: Sonal Porwal, Deepali Vora |
10.5120/12210-8319
|
Sonal Porwal, Deepali Vora . A Naive Gain Approach to Intrusion Detection Systems. International Journal of Computer Applications. 70, 23 ( May 2013), 35-39. DOI=10.5120/12210-8319
Abstract
Today the world is dependent upon so many advanced technologies and network systems, that their protection from those which intent to break the system with malicious attacks, or trying some unauthorized access with an intention of financial gain or simply trying to intrude the system has become essential. This leads to the need of Intrusion Detection Systems. Many algorithms have been suggested to implement this system, which requires building of a training model by using a training data set. In this paper,NSL KDD data set will be used to train the system using Naïve Bayes approach and then there is an attempt to improve its accuracy by proposing an algorithm based on feature selection. A concept of threshold is also introduced which works on the principle of C4. 5 algorithm. The proposed algorithm is applied on another data set that is supplied by the user which is also a part of NSL KDD. This paper discusses the proposed algorithm which is used to improve the performance of the classification system of the Naïve Bayes Classifier and reduce the number of false alarm rate to some extent.
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