Citation:
M. Ozkutuk S.S Chirayath, “Vulnerability Assessment of a Physical Protection System Design Using a Multi Path Analysis and Moving Critical Detection Points”, INMM/ESARDA Joint Annual Meeting, 22-26 May 2023, Vienna, Austria.
Abstract:
A modified Monte-Carlo-based multi-path method was developed to assess the probability of interruption (PI) offered by a physical protection system (PPS) at a nuclear facility against an adversary attacking the facility. To perform a multi-path analysis based on an adversary sequence diagram (ASD), a stochastic approach (Monte Carlo) software code was developed. Three types of distributions (Gaussian, Poisson, and Uniform) were used to determine the differences in choosing the values of probability of detection (PD) provided by the PPS elements in the analysis of adversary interruption. The multi-path analysis approach presented in this study was not limited to the adversary’s single path analysis approach unlike the deterministic approach used in the estimate adversary sequence interruption (EASI) model. EASI model does not estimate uncertainty value that is needed to represent the actual level of performance of the PPS. Moreover, in this model, the critical detection point (CDP) was not fixed at the same protection layer for all attack scenarios as in the case of EASI model. Instead, CDP was moved to enable the analysis of the different types of actions adversaries take to achieve their goals based on their perception of the PPS. These adversary actions consist of random, rushing, covert, deep penetration, and most vulnerable path (MVP) strategies. The software developed was enabled to move the CDP, which was updated depending on the paths selected by the adversary. This type of CDP movement resulted in more realistic PI values and the corresponding uncertainties. Also modeled in the code was the threats from insiders by eliminating the corresponding detection or delay elements of the PPS for the chosen adversary path. The price of each PPS element such as sensors and cameras was integrated into the software code. Taking into consideration the unit price of the detection elements, the relationship between cost and PI was examined. As a result of sampling PD values from three different distributions, the corresponding PI values and their uncertainties were compared for each sampling strategy.