Projection of Cyber Attacks using Damage Estimation and Combination of Attacker’s Capability and Opportunity based on Transferable Belief Model

"Nowadays there are so many tools available for capturing the events and alerts within networks. The need for a system that could aggregate the information generated by these tools and combine them to make    better decisions is strongly acknowledged. If we could predict cyber attacks and estimate their effects     before they actually occur, we would be able to apply a better defense strategy and reduce the damage to our critical assets. The projection of cyber attacks is to predict them based on a certain framework using mathematical methods. One of these methods is the Transferable Belief Model (TBM). In this paper, we used the TBM to combine capability and opportunity of attackers - which are cyber attacks' projection  components- to project the future situation of attacks. We have also tested our results against our  customized high-level attack tracks dataset. The result of comparison between our algorithm and the  previously presented algorithm at the Information Fusion Centre of Malek-Ahstar University of Technology shows an average improvement of 7%.