A PROBABILISTIC APPROACH TO RISK FORMALIZATION IN PHYSICAL PROTECTION SYSTEMS FOR SPECIAL PURPOSE FACILITIES

Physical protection systems for special purpose facilities operate under conditions in which uncertainty, scenario variability, and differentiated exposure of critical elements significantly affect the adequacy of security assessment. Under such conditions, deterministic approaches based on fixed threat and protection parameters are not sufficient for decision-oriented risk analysis, especially in facilities where hostile actions may be intentional, adaptive, and operationally timed. The aim of this study is to develop a probabilistic framework for the formalization of risk in physical protection systems for special purpose facilities. The proposed approach treats risk not as an aggregate property of the protected object as a whole, but as a scenario based and critical element specific quantity formed through the interaction of threat realization probability, vulnerability, and consequence severity. The study systematizes the main sources of uncertainty affecting physical protection assessment, including variability of damaging factors, spatial uncertainty, uncertainty of adversary intent and capability, and changes in operational conditions. A structured system of input parameters is proposed, covering threat source and scenario descriptors, damaging factor intensity and dynamics, critical thresholds, spatial and temporal variables, and indicators of detection, delay, response, and command and control subsystems. The framework also incorporates Bayesian updating to revise the probability component when new operational information becomes available, thereby transforming risk from a static estimate into a dynamic decision support variable. In addition, interpretable parameter identification and sensitivity analysis are introduced to support model transparency and prioritization of protective measures under resource constraints. The results show that the proposed framework provides a more adequate methodological basis for physical protection assessment than undifferentiated deterministic approaches because it allows explicit representation of uncertainty, scenario specific differentiation, critical element level analysis, and subsystem-oriented prioritization. The study concludes that probabilistic risk formalization offers a scientifically grounded and operationally relevant basis for the design, evaluation, and improvement of physical protection systems for special purpose facilities, including military facilities operating in adaptive threat environments.