Multi-Perspective Security Risk Assessment for APT Attacks in CPS Environments

In today’s rapidly evolving digital landscape, organizations confront increasingly sophisticated cyber threats with profound political, economic, and social implications. Among them, Advanced Persistent Threats (APTs) are particularly critical due to their persistence, strategic intent, and multi-stage lifecycles that compromise diverse assets while evading detection. Meanwhile, the emergence of cyber-physical-social (CPS) systems has created complex environments in which cyber, physical, and social domains are tightly interlinked. Traditional approaches—such as attack trees, attack patterns, cyber kill-chain models, and conventional risk assessment methods—remain limited, as they emphasize technology-level analysis and isolated countermeasures and fail to adequately capture multi-layered dependencies and adaptive APT behavior. To address these limitations, this study proposes a unified security risk assessment framework for CPS environments. The framework integrates four key components: (1) knowledge-based APT attack scenario generation and TTP-driven threat modeling; (2) construction of a Mission-Critical Target System (MCTS) comprising vertically and horizontally interconnected layers with extended criticality evaluation; (3) adaptive security requirements engineering to support continuous identification, specification, and refinement of defense measures; and (4) evidence-based risk assessment that incorporates technical, organizational, and social interdependencies to enable iterative, layered defense planning. Ontology-supported knowledge representation is employed to structure threats, assets, and security requirements and to improve traceability and auditability, while risk likelihoods are updated through evidence-driven evaluation rather than automated semantic inference. Validated through theoretical analysis and empirical case studies, the framework effectively captures the dynamic and multidimensional characteristics of APT behavior in CPS contexts and demonstrates improved comprehensiveness, precision, adaptability, and practical relevance compared with traditional assessment approaches.