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A Novel Model for Vulnerability Analysis through Enhanced Directed Graphs and Quantitative Metrics.

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Summary
This summary is machine-generated.

This study introduces an Extended Dependency Graph (EDG) model to track industrial component vulnerabilities over time. The model aids in prioritizing patching and identifying security requirements for Industry 4.0 systems.

Keywords:
CAPECCPECVECVSSCWEIACSIEC 62443OpenPLCcybersecuritydirected graphsecurity metricsvulnerability assessment

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Area of Science:

  • Cybersecurity Engineering
  • Industrial Control Systems Security
  • Software Vulnerability Analysis

Background:

  • Industry 4.0 and 5G connectivity increase cybersecurity risks in industrial components.
  • Component vulnerabilities necessitate complex and costly secure design and lifecycle management.
  • Proactive vulnerability analysis is crucial for maintaining industrial system integrity.

Purpose of the Study:

  • To present a novel model for analyzing industrial component vulnerabilities throughout their lifecycle.
  • To provide a method for tracking, prioritizing, and mitigating cybersecurity risks.
  • To support the development of more secure industrial systems.

Main Methods:

  • Development of the Extended Dependency Graph (EDG) model.
  • Utilizing a directed graph for component structure and Common Vulnerability Scoring System (CVSS) metrics.
  • Applying the EDG model to analyze vulnerabilities in the OpenPLC project.

Main Results:

  • The EDG model effectively tracks vulnerabilities over a device's lifespan.
  • Analysis of OpenPLC revealed memory buffer operation vulnerabilities concentrated in the libssl library.
  • The model successfully identified new requirements and generated relevant test cases.

Conclusions:

  • The EDG model offers a robust framework for continuous vulnerability management in industrial components.
  • Vulnerability analysis using EDG aids in targeted patching and security enhancement.
  • This approach supports the secure evolution of Industry 4.0 infrastructure.