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Related Experiment Videos

OntoSecAI: Ontology-driven security automation for AI-enabled systems.

Ubaid Ullah1, Muhammad Haleem2, Asad Ullah3

  • 1IMT School for Advanced Studies, Lucca, Italy.

Plos One
|December 18, 2025
PubMed
Summary

This study introduces OntoSecAI, an ontology-based approach for automated artificial intelligence (AI) threat modeling. It addresses AI security risks by providing consistent risk assessments and a unified knowledge base for diverse AI systems.

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Area of Science:

  • Computer Science
  • Artificial Intelligence Security

Background:

  • Artificial intelligence (AI) models introduce security risks, including malicious data exploitation.
  • AI-based threat modeling research is limited by data representation, inference rule, and assessment challenges.
  • Insufficient stakeholder AI and security expertise leads to inaccurate threat modeling.

Purpose of the Study:

  • To develop and implement OntoSecAI, an ontology-based approach for automated threat modeling and assessment of AI-enabled systems.
  • To address limitations in formal data representation, automated threat identification, and consistent risk assessment for AI security.

Main Methods:

  • Designed three ontologies and 30 inference rules for AI security and data representation.
  • Implemented risk and CVSS-based vulnerability assessments for comprehensive threat modeling.
  • Validated the approach through 10 case studies and verified using mathematical theorems.

Main Results:

  • Ontologies facilitate unified representation and comprehensive data coverage for security and AI systems.
  • Inference rules effectively map system assets to potential security threats.
  • Ontology utilization ensures consistent risk and vulnerability assessments across AI systems.

Conclusions:

  • OntoSecAI provides a comprehensive security knowledge base for stakeholders with varying expertise.
  • The approach ensures uniform threat modeling across diverse AI systems.
  • OntoSecAI enhances adaptability to emerging security threats in AI.