Читать книгу Intelligent Network Management and Control - Badr Benmammar - Страница 23

A Bayesian network is a probabilistic graphical model representing a set of random variables in the form of an acyclic oriented graph. This technique is generally used for intrusion detection in combination with statistical diagrams. It has several advantages, notably the capacity to code the interdependences between variables and to predict events, as well as the possibility of integrating both previous knowledge and previous data (Heckerman 2008). Its major drawback is that results are comparable to statistical techniques, but this requires additional computation efforts. Kruegel et al. (2003) proposed a multisensor fusion approach using a Bayesian network–based classifier for the classification and cancellation of false alarms, according to which the outputs of various sensors of the intrusion detection system are aggregated to generate a single alarm. Han et al. (2015) proposed an intrusion detection algorithm based on Bayesian networks relying on the analysis into main components. The authors calculate the characteristic data value of the attack on the original network, and then extract the main properties by analysis into main components.