This paper introduces a new Bayesian network structure, named a Partial Bayesian Network (PBN), and describes an algorithm for constructing it. The PBN is designed to be used for classification tasks, and accordingly the algorithm constructs an approximate Markov blanket around a classification node. Initial experiments have compared the performance of the PBN algorithm with Naïve Bayes, Tree-A...

The success and popularity of naive Bayes has led to a field of research exploring algorithms that seek to retain its numerous strengths while reducing error by alleviating the attribute interdependence problem. This thesis builds upon this promising field of research, contributing a systematic survey and several novel and effective techniques. It starts with a study of the strengths and weakne...

One of the major security challenges in cloud computing is the detection and prevention of intrusions and attacks. In order to detect and prevent malicious activities at the network layer, we propose a security framework which integrates a network intrusion detection system (NIDS) in the Cloud infrastructure. We use snort and Bayesian classifier machine learning based techniques to implement th...