Visible to the public A Meta Language for Threat Modeling and Attack Simulations

TitleA Meta Language for Threat Modeling and Attack Simulations
Publication TypeConference Paper
Year of Publication2018
AuthorsJohnson, Pontus, Lagerström, Robert, Ekstedt, Mathias
Conference NameProceedings of the 13th International Conference on Availability, Reliability and Security
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-6448-5
KeywordsAttack Graphs, composability, Cyber Dependencies, cyber security, domain specific language, Metrics, pubcrawl, resilience, Resiliency, threat modeling

Attack simulations may be used to assess the cyber security of systems. In such simulations, the steps taken by an attacker in order to compromise sensitive system assets are traced, and a time estimate may be computed from the initial step to the compromise of assets of interest. Attack graphs constitute a suitable formalism for the modeling of attack steps and their dependencies, allowing the subsequent simulation. To avoid the costly proposition of building new attack graphs for each system of a given type, domain-specific attack languages may be used. These languages codify the generic attack logic of the considered domain, thus facilitating the modeling, or instantiation, of a specific system in the domain. Examples of possible cyber security domains suitable for domain-specific attack languages are generic types such as cloud systems or embedded systems but may also be highly specialized kinds, e.g. Ubuntu installations; the objects of interest as well as the attack logic will differ significantly between such domains. In this paper, we present the Meta Attack Language (MAL), which may be used to design domain-specific attack languages such as the aforementioned. The MAL provides a formalism that allows the semi-automated generation as well as the efficient computation of very large attack graphs. We declare the formal background to MAL, define its syntax and semantics, exemplify its use with a small domain-specific language and instance model, and report on the computational performance.

Citation Keyjohnson_meta_2018