A Survey of MulVAL Extensions and Their Attack Scenarios Coverage

August 11, 2022 ยท The Cartographer ยท ๐Ÿ› IEEE Access

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: A Survey of MulVAL Extensions and Their Attack Scenarios Coverage"

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Authors David Tayouri, Nick Baum, Asaf Shabtai, Rami Puzis arXiv ID 2208.05750 Category cs.CR: Cryptography & Security Citations 33 Venue IEEE Access Last Checked 2 days ago
Abstract
Organizations employ various adversary models in order to assess the risk and potential impact of attacks on their networks. Attack graphs represent vulnerabilities and actions an attacker can take to identify and compromise an organization's assets. Attack graphs facilitate both visual presentation and algorithmic analysis of attack scenarios in the form of attack paths. MulVAL is a generic open-source framework for constructing logical attack graphs, which has been widely used by researchers and practitioners and extended by them with additional attack scenarios. This paper surveys all of the existing MulVAL extensions, and maps all MulVAL interaction rules to MITRE ATT&CK Techniques to estimate their attack scenarios coverage. This survey aligns current MulVAL extensions along unified ontological concepts and highlights the existing gaps. It paves the way for methodical improvement of MulVAL and the comprehensive modeling of the entire landscape of adversarial behaviors captured in MITRE ATT&CK.
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