Refinement-Aware Generation of Attack Trees

Abstract

Attack trees allow a security analyst to obtain an overview of the potential vulnerabilities of a system. Due to their refinement structure, attack trees support the analyst in understanding the system vulnerabilities at various levels of abstraction. However, contrary to manually synthesized attack trees, automatically generated attack trees are often not refinement-aware, making subsequent human processing much harder. The generation of attack trees in which the refined nodes correspond to semantically relevant levels of abstraction is still an open question. In this paper, we formulate the attack-tree generation problem and propose a methodology to, given a system model, generate attack trees with meaningful levels of abstraction.