Title of article :
Bayesian based intrusion detection system
Author/Authors :
Altwaijry, Hesham King Saud University - Computer Engineering Department, Saudi Arabia , Algarny, Saeed King Saud University - Computer Engineering Department, Saudi Arabia
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.
Keywords :
Intrusion detection system (IDS) , Bayesian filter , KDD ’99
Journal title :
Journal Of King Saud University - Computer and Information Sciences
Journal title :
Journal Of King Saud University - Computer and Information Sciences