A Decision Support System for Optimal Security Posture via Defensive Measures Prioritization

This thesis addresses the critical challenge of adopting an optimal security posture in an increasingly complex threat environment. As organizations face sophisticated cyber threats across evolving technology landscapes, security practitioners require systematic approaches for prioritizing defensive measures and selecting appropriate security mechanisms beyond manual selection methods. To address this gap, this research introduces an innovative framework that leverages the MITRE D3FEND ontology and MITRE ATT&CK framework to provide recommendations and guidance aimed at improving security posture against a given threat landscape. Through case studies focused on ransomware and cloud-native infrastructures, the research demonstrates that the framework effectively identifies prioritized defensive measures between distinct attack vectors while maintaining defensive coverage across the threat spectrum. Comparative analysis confirms the ability of the system to adapt recommendations based on unique scenario characteristics while maintaining coverage of foundational security controls. Overall, this work represents an advancement in threat-informed defense planning for organizations facing evolving cyber threats in increasingly complex environments.