Review, Meta-Taxonomy, and Use Cases of Cyberattack Taxonomies of Manufacturing Cybersecurity Threat Attributes and Countermeasures

TL;DR

This paper systematically reviews and synthesizes existing cyberattack taxonomies in manufacturing, creating a comprehensive meta-taxonomy to improve threat understanding, detection, and mitigation strategies in smart manufacturing systems.

Contribution

It develops a unified meta-taxonomy of manufacturing cyberattack attributes and countermeasures, addressing inconsistencies and gaps in existing taxonomies, and proposes practical use cases for cybersecurity enhancement.

Findings

Compiled and analyzed existing taxonomies into a comprehensive meta-taxonomy.

Identified gaps and overlaps in current attack taxonomies.

Suggested future directions and practical applications for cybersecurity in manufacturing.

Abstract

A thorough and systematic understanding of different elements of cyberattacks is essential for developing the necessary tools to prevent, detect, diagnose, and mitigate cyberattacks in manufacturing systems. In response, researchers have proposed several attack taxonomies as methods for recognizing and categorizing various cyberattack attributes. However, those taxonomies cover selected attack attributes depending on the research focus, sometimes accompanied by inconsistent naming and definitions. These seemingly different taxonomies often overlap and can complement each other to create a comprehensive knowledge base of cyberattack attributes that is currently missing in the literature. Additionally, there is a missing link from creating structured knowledge by using a taxonomy to applying this structure for cybersecurity tools development and aiding practitioners in using it. To tackle these challenges, this article highlights how cyberattack taxonomies can be used to better understand and characterize manufacturing cybersecurity threats. It also reviews and analyzes current taxonomical classifications of manufacturing cybersecurity threat attributes and countermeasures, as well as the proliferation of the scope and coverage in existing taxonomies. As a result, these taxonomies are compiled into a more comprehensive and consistent meta-taxonomy for the smart manufacturing space. The resulting meta-taxonomy provides a holistic analysis of current taxonomies and integrates them into a unified structure. Based on this structure, this paper identifies gaps in current attack taxonomies and provides directions for future improvements. Finally, the paper introduces potential use cases for attack taxonomies in smart manufacturing systems for assessing security threats and their associated risks, devising risk mitigation strategies, and informing the application of cybersecurity frameworks.