DAG-Based Attack and Defense Modeling: Don't Miss the Forest for the Attack Trees

TL;DR

This survey reviews DAG-based attack and defense modeling techniques, comparing over 30 methodologies, and provides guidance on selecting appropriate methods based on specific security modeling needs.

Contribution

It offers a comprehensive overview, taxonomy, and comparison of DAG-based security modeling approaches, aiding practitioners in choosing suitable techniques.

Findings

Summarizes 30+ DAG-based security modeling methodologies.

Provides a taxonomy of attack and defense modeling formalisms.

Guides selection of modeling techniques based on user requirements.

Abstract

This paper presents the current state of the art on attack and defense modeling approaches that are based on directed acyclic graphs (DAGs). DAGs allow for a hierarchical decomposition of complex scenarios into simple, easily understandable and quantifiable actions. Methods based on threat trees and Bayesian networks are two well-known approaches to security modeling. However there exist more than 30 DAG-based methodologies, each having different features and goals. The objective of this survey is to present a complete overview of graphical attack and defense modeling techniques based on DAGs. This consists of summarizing the existing methodologies, comparing their features and proposing a taxonomy of the described formalisms. This article also supports the selection of an adequate modeling technique depending on user requirements.