MAPPS: A stochastic computational tool for multi-path analysis of physical protection systems

Yanuar A. Setiawan, Sunil S. Chirayath, Evans D. Kitcher

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

We present a new stochastic computational tool, Multi-path Analysis of Physical Protection Systems (MAPPS) useful for Physical Protection System (PPS) effectiveness analysis. MAPPS tool can perform multi-path (adversary paths) analysis using an Adversary Sequence Diagram (ASD) and can determine the Most Vulnerable Path (MVP). The MVP determination by MAPPS uses the concept of Critical Detection Point (CDP). Suitability of MAPSS for PPS design effectiveness analysis is confirmed through an example. A comparison of MAPPS results with the traditional single path analysis (employing the Estimate of Adversary Sequence Interruption-EASI model) shows the advantages of using MAPPS. MAPPS correctly predicts the MVP and the distribution of probability of interruption (PI) values for various adversary strategies including collusion with facility insiders. MAPPS results show that a focusing only on mean of PI value distribution may not be appropriate instead, a analyzing the low probability tail of the PI distribution is important.

Original languageEnglish
Article number107074
JournalAnnals of Nuclear Energy
Volume137
DOIs
StatePublished - Mar 2020
Externally publishedYes

Keywords

  • EASI
  • Insider threat
  • Multi-path analysis
  • Physical Protection System
  • Probability of interruption
  • Stochastic

Fingerprint

Dive into the research topics of 'MAPPS: A stochastic computational tool for multi-path analysis of physical protection systems'. Together they form a unique fingerprint.

Cite this