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

arXiv: https://arxiv.org/abs/1303.7397 · HTML: https://mlsanity.com/paper/1303.7397/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Mar 2013.

## Built on by (most cited first, 2 of 2)

- [GRAVITAS: Graphical Reticulated Attack Vectors for Internet-of-Things Aggregate Security](https://mlsanity.com/paper/2106.00073/) (2021)
- [Towards the generation of hierarchical attack models from cybersecurity vulnerabilities using language models](https://mlsanity.com/paper/2410.05351/) (2024)

## Abstract (arXiv)

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.