Reduced realistic attack plan surface for identification of prioritized attack goals

Current homeland cyber security practices and techniques focus on identifying weakness, aggregating data in the hope of improving incident detection and promoting information sharing with the public. These foci emphasize a broad collection of knowledge of what could happen to minimize damage and urge the implementation of a frequently growing list of specific actions to reduce vulnerability exposures. Large-scale “big data” extraction and processing challenges ensue from the need to understand each device vulnerability within the context of every environment. Conversely, an attacker needs only to identify a single attack vector to elicit a compromise. Our paper describes 1) a more efficient approach to proactively securing devices using an Attack Plan Generator, 2) how we transform vulnerability and defect databases into attack surface representations and 3) how those representations provide a much more effective perspective into how an attacker would seek to compromise a given device.