A Structuration Approach to Theorizing Cybersecurity Practice: The STARC Model

The problem: Cybersecurity practice runs simultaneously across analysts, teams, organizations, sectors, and regulators, co-evolves with adversaries, and increasingly blends human and algorithmic decision-making. The theories applied to it operate at single organizational levels and cannot explain why organizations with broadly similar controls differ sharply in resilience. This paper: We develop STARC (Structuration Theory Adaptation for Resilient Cybersecurity), a framework for locating where cybersecurity practice succeeds or fails structurally. It extends Giddens' Structuration Theory with three innovations, Multi-Level Adversarial Agency, Threat-Adaptive Structuration, and Material-Agential Structural Properties, across five structure-agency triads. Evidence base: STARC is illustrated through re-analysis of three financial organizations, an Australian, an Indonesian, and a Malaysian bank, across 20 interviews from SOC analysts to senior executives, selected as diverse insourced and outsourced configurations rather than as a comparison of equivalents. Cybersecurity contribution: STARC offers a structural account of why differently resourced and outsourced organizations differ in resilience, and a vocabulary for diagnosing incident-response breakdown across levels, tempos, and the human-algorithm authority boundary that single-level frameworks leave invisible. Theory and outputs: It extends Structuration Theory to adversarial, multi-level, and hybrid human-algorithmic contexts, and yields seven testable propositions linking structuration to resilience, offered for future testing.