Use of Naive Bayesian Filtering in the Intrusion Detection System (IDS)

Recently, the main critical part of all organizational data systems is the security since it is threatened by several network attacks which in turn influences on the world financial system. Thus, the most used system in dealing with networks problems is the Intrusion Detection System (IDS). It is used to monitor the system performance and send alerts when there is anomalous activity existence in which the administrator of the system should respond to these alerts rapidly. In this paper, we proposed a statistical Naïve Bayesian method which will be used in the Intrusion Detection Systems ( IDS) systems in different scenarios such as analyzing the HTTP service based traffic and identify the HTTP normal connections and attacks. On the other hand, a comparative study between them based on the performance parameters will be analyzed in order to determine the most effective and efficient statistical method in detecting various types of attacks.