Sustainable development of smart regions: a set theoretic data model for assessing the cyber resilience of critical infrastructure entities

Abstract

The increasing complexity and intensity of cyber threats to critical infrastructure entities (CIE) necessitate a transition from classical protection methods to comprehensive cyber resilience strategies. The aim of this research is to create a formal mathematical toolkit for assessing the ability of infrastructure entities to anticipate attacks, withstand them, recover, and adapt to changes. This work proposes a set-theoretic data model (STDM) that, for example, generalizes and formalizes the hierarchical structure of the MITRE Cyber Resiliency Engineering Framework (CREF). The research methodology is based on the introduction of sets of identifiers for goals, objectives, sub-objectives, and basic resilience measures, as well as on the development of a unique indexing system for their unambiguous mapping. The modeling results create a rigorous mathematical foundation for systematic cyber resilience analysis, enabling the identifycation of protection gaps and informed resource prioritization. For instance, the generalization of CREF through a set-theoretic approach ensures high model flexibility to dynamic changes in the threat landscape and specific requirements of different types of CIE. It is concluded that the implementation of the model directly contributes to the long-term reliability and ensures the effectiveness of sustainable development of critical infrastructure in smart regions, aligning with the UN Sustainable Development Goals (SDGs 9 and 11) in the context of building resilient and secure socio-technical systems.

Keywords: sustainable development, smart regions, cyber resilience, critical infrastructure entities, set-theoretic data model, MITRE CREF, resilience assessment, decision support.