Threat Informed Defence Engineering Models for Measuring Security Control Effectiveness at Scale

Modern enterprises operate within increasingly complex, distributed, and adversarial digital environments, where traditional compliance-driven security metrics fail to capture the true effectiveness of defensive controls. As cyber threats evolve in sophistication, frequency, and automation, organizations face mounting pressure to measure how well their security controls actually reduce adversary capability, limit attack progression, and protect mission-critical assets at scale. Threat-informed defence has emerged as a paradigm that aligns security architecture, detection, and response capabilities with empirically observed adversary behaviours rather than abstract risk assumptions or static control checklists. This paper examines advances in threat-informed defence engineering models for measuring security control effectiveness across large, heterogeneous environments. Drawing exclusively on literature and frameworks established, the study synthesizes research from cybersecurity engineering, adversary emulation, control validation, cyber risk measurement, and large-scale security operations. The paper analyses how threat intelligence, adversary tactics, techniques, and procedures (TTPs), and operational telemetry can be integrated into engineering models that quantify control coverage, detection efficacy, response latency, and adversary disruption. A structured conceptual perspective is developed to highlight methodological trends, limitations, and research gaps in scaling threat-informed measurement across complex enterprise and critical infrastructure environments. The study contributes to ongoing efforts to move cybersecurity measurement from compliance-oriented indicators toward evidence-based, adversary-centric performance assessment.