Open AccessThe Development Of Multi-Path Adversary Analysis Tool For Vulnerability Assessment of Physical Protection Systems (MAVA)
Author(s) -
Dinan Andiwijayakusuma,
A Mardhi,
T Setiadipura,
Acep Purqon,
Zaki Su’ud
Publication year - 2021
Publication title -
journal of engineering and scientific research
Language(s) - English
Resource type - Journals
ISSN - 2685-1695
DOI - 10.23960/jesr.v3i2.92
Subject(s) - adversary , vulnerability assessment , vulnerability (computing) , computer science , python (programming language) , path (computing) , computer security , path analysis (statistics) , computer network , operating system , machine learning , psychology , psychological resilience , psychotherapist
. 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.