International Journal of Academic Multidisciplinary Research (IJAMR)   Year: 2020 | Volume: 4 | Issue: 5 | Page No.: 1-8 A Casual Network Based System for Predicting Multi-stage Attack with Malicious IP Alile Solomon Osarumwense , Egwali Annie Oghenerukevbe Abstract: Multi-stage attacks are attacks executed in phases where each phase of the attack solely relies on the completion of the preceding phase. These attacks are so cleverly designed that they are able to elude detection from most network instruction detection systems and they are capable of infiltrating sophisticated defenses. In this paper, we proposed and designed a probabilistic inference system for predicting Multi-stage attack with malicious IP based on a supervised machine learning technique called Casual Network; otherwise known as Bayesian Belief Network (BBN) Model. The BBN model was designed on Unbbayes Simulator. The fusion of the proposed inference system and BBN model will assist in the prediction of perpetrated multi-stage attacks from computing devices and its means of identification on a computer network (IP address) before the completion of the said attack and hence help reduce the effects of this kind of attacks on networks by providing information which can be used as a measure to safeguard against this kind of stylish attack.