The Development Of Multi-Path Adversary Analysis Tool For Vulnerability Assessment of Physical Protection Systems (MAVA)

Authors

  • D Andiwijayakusuma
  • A Mardhi Center for Nuclear Reactor Technology and Safety, Badan Tenaga Nuklir Nasional, Gedung 80 Kawasan PUSPIPTEK
  • T Setiadipura Center for Nuclear Reactor Technology and Safety, Badan Tenaga Nuklir Nasional, Gedung 80 Kawasan PUSPIPTEK
  • A Purqon Earth Physics and Complex System Research Division, Department of Physics, Institut Teknologi Bandung Gedung Fisika
  • Z Suud Nuclear Physics and Bio Physics Research Division, Department of Physics, Institut Teknologi Bandung Gedung Fisika

DOI:

https://doi.org/10.23960/jesr.v3i2.92

Keywords:

PPS, multi-path analysis, nuclear security

Abstract

Abstract. The Physical Protection System (PPS) is an important component in each nuclear facility security aspect. We must regularly evaluate the effectiveness of PPS to ensure the system can anticipate every enemy attack; therefore, a PPS vulnerability assessment is needed. In this study, we develop a Multi-path Analysis tool for Vulnerability Assessment of PPS (MAVA) based on the Adversary Sequence Diagram (ASD) implemented in python computer code. We examined for feasibility by applying the code to a hypothetical facility (National Nuclear Research Facility - NNRF). The results of calculations compared to single-path analysis (EASI) show the advantages of MAVA, which can calculate the probability of interruption simultaneously on multi-path analysis. MAVA also predict the adversary's most vulnerable paths (MVP) with its various strategies for intrusion path. MAVA results show that multi-path calculations help analysts obtain information faster in evaluating to improve the effectiveness of PPS.

 

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Published

2021-12-15

How to Cite

Andiwijayakusuma, D., Mardhi, A., Setiadipura, T., Purqon, A., & Suud, Z. (2021). The Development Of Multi-Path Adversary Analysis Tool For Vulnerability Assessment of Physical Protection Systems (MAVA). Journal of Engineering and Scientific Research, 3(2). https://doi.org/10.23960/jesr.v3i2.92

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Articles