| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 483684 | Journal of King Saud University - Computer and Information Sciences | 2012 | 6 Pages |
Abstract
In this paper an intrusion detection system is developed using Bayesian probability. The system developed is a naive Bayesian classifier that is used to identify possible intrusions. The system is trained a priori using a subset of the KDD dataset. The trained classifier is then tested using a larger subset of KDD dataset. The Bayesian classifier was able to detect intrusion with a superior detection rate.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Hesham Altwaijry, Saeed Algarny,