A Governance Architecture for Agentic Adversary Detection: Operator Archetypes, Drift Matrices, Governance Physics, the Cascade Engine, and the Friction-Intelligence App

This paper presents the solution architecture companion to the ontology gap diagnosis established inTruong (2026, DOI 10.5281/zenodo.19007096). Having argued that the cybersecurity detectiondiscipline lacks the conceptual scaffolding required to detect adversaries that reason, replan, andcoordinate across layers toward goals, this paper introduces a five-component governancearchitecture designed to fill that gap. The five components — Operator Archetypes, Drift Matrices,Governance Physics / Boundary Hygiene, the Cascade Engine, and the Friction-Intelligence App —form a unified ontology for detecting, interpreting, and constraining agentic behavior acrossbehavioral, operational, and substrate layers. Together they address the two structural missingpillars identified in the companion submission: model-as-substrate governance and cross-layerintent composition. This paper provides canonical definitions, structural diagrams, and a frameworkarchitecture overview for each component. Implementation logic, threshold values, andinter-framework weighting relationships are not published.