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◆ ГРААЛЬ НАУКИ2026-04-12· Risk analysis (engineering)

INTEGRAL SENSITIVITY INDICATOR BASED ON MULTILAYER INDICATORS FOR CRITICAL INFRASTRUCTURE AND SPECIAL-PURPOSE FACILITIES AND THE SELECTION OF MEASURES

Aziz Talibov, Ramil Akhundov, Elshan HASHIMOV

原始摘要(英文原文)· Original abstract
This article develops a methodological framework for assessing the vulnerability of critical infrastructure and special-purpose facilities to hybrid threats on the basis of a multilayer indicator system and an integral vulnerability indicator. The study proceeds from the premise that hybrid threats affect facilities through interrelated physical, cyber, organizational, and information-impact layers, which makes purely qualitative assessment insufficient for decision support. The proposed approach integrates indicator passportization, normalization, weighting, and aggregation in order to transform heterogeneous security parameters into a unified analytical space suitable for comparison, monitoring, and prioritization. In addition to the vulnerability indicator, the framework introduces a complementary resilience representation and formulates the selection of protective measures as a constrained portfolio optimization problem under budget, time, and minimum required resilience conditions. The methodology also incorporates a scenario-based logic that compares baseline and worst-case conditions, thereby improving the robustness of decisions under uncertainty. The results show that the proposed framework can support not only the diagnosis of multilayer weaknesses, but also the justified selection of a coordinated set of measures with the highest marginal contribution to overall resilience. The practical significance of the study lies in providing a traceable and auditable decision-support mechanism for the adaptive protection of critical infrastructure and special-purpose facilities against complex hybrid threats.
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INTEGRAL SENSITIVITY INDICATOR BASED ON MULTILAYER INDICATORS FOR CRITICAL INFRASTRUCTURE AND SPECIAL-PURPOSE FACILITIES AND THE SELECTION OF MEASURES — 科研速览 Science Skim