A Workflow for Distributed and Resilient Attack Graph Generation.

Among the existing attack models, Attack Graphs (AGs) represent a powerful abstraction to capture the notion of multi-step attacks i.e., ensembles of sequential vulnerability exploits taken by an attacker with a specific objective. A well-known issue in using AGs is their poor scalability due to the complexity of generating and analyzing all existing attack paths. To this aim, we propose a workflow for a more efficient generation of attack paths in a distributed and resilient manner. We describe the general workflow, emphasizing the research challenges and providing few preliminary solutions.