Optimizing physical protection system using domain experienced exploration method

• Main Authors: Dejan Čakija, Željko Ban, Marin Golub, Dino Čakija
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2020-04-01
• Series: Automatika
• Subjects: multi-objective optimization of physical protection system; domain experienced exploration; genetic algorithms; pps design; numerical vulnerability analysis
• Online Access: http://dx.doi.org/10.1080/00051144.2019.1698192

Assessing physical protection system efficiency is mostly done manually by security experts due to the complexity of the assessment process and lack of tools. Computer aided numerical vulnerability analysis has been developed to quantitatively assess physical protection systems. A variety of methods have been proposed to optimize physical protection systems, where one of the most advanced approaches entails precisely defining which security components should be selected and where they should be placed at protected facilities, taking into consideration adversary type, to maximize the probability that an adversary will be stopped at minimum system cost. The most computationally intensive part of the optimization process is the evaluation. The evaluation involves recreating search space and finding optimal adversary’s attack paths from each entry point. We present the domain experienced exploration method that optimizes evaluation process during the search for optimum solutions, considering results from previous evaluations. Performed experiments show that using the presented method, in real-world domains, results in a reduction of evaluation iterations.