Defensive Cyber Battle Damage Assessment Through Attack Methodology Modeling

Due to the growing sophisticated capabilities of advanced persistent cyber threats, it is necessary to understand and accurately assess cyber attack damage to digital assets. This thesis proposes a Defensive Cyber Battle Damage Assessment (DCBDA) process which utilizes the comprehensive understanding of all possible cyber attack methodologies captured in a Cyber Attack Methodology Exhaustive List (CAMEL). This research proposes CAMEL to provide detailed knowledge of cyber attack actions, methods, capabilities, forensic evidence and evidence collection methods. This product is modeled as an attack tree called the Cyber Attack Methodology Attack Tree (CAMAT). The proposed DCBDA process uses CAMAT to analyze potential attack scenarios used by an attacker. These scenarios are utilized to identify the associated digital forensic methods in CAMEL to correctly collect and analyze the damage from a cyber attack. The results from the experimentation of the proposed DCBDA process show the process can be successfully applied to cyber attack scenarios to correctly assess the extent, method and damage caused by a cyber attack.