Evaluation of vulnerable path: Using heuristic path-finding algorithm in physical protection system of nuclear power plant

doi:10.1016/j.ijcip.2018.08.006

International Journal of Critical Infrastructure Protection

Volume 23, December 2018, Pages 90-99

https://doi.org/10.1016/j.ijcip.2018.08.006 Get rights and content

Abstract

A novel heuristic path-finding method named “Heuristic Path-finding for the Evaluation of PPS effectiveness, HPEP” was proposed for the evaluation of a vulnerable intrusion path in Physical Protection System (PPS). According to the design basis threat (DBT), HPEP takes the detection probability and interruption probability as heuristic information to analyze the vulnerable adversary path. Moreover, HPEP can find the shortest path for the response force to reach the target in the first attempt and guarantees interruption of an adversary intrusion. Three types of simulation experiments are studied for the feasible analysis of HPEP method. The analysis of main parameters in the simulation results will provide detailed and comprehensive technical information for the redesign and upgrade of the PPS.

Introduction

A Physical Protection System (PPS) (also called security system) integrates people, procedures, and equipment to protect assets and facilities against theft, sabotage, and other malevolent human attacks [1]. The main threats for nuclear materials and facilities are however natural disasters rather than malicious human actions since human adversaries must learn and adapt to intrude nuclear power plants (NPPs). The security of nuclear materials and facilities became key protection objects for most countries in the 1970 s, and some relevant conventions on the PPS entered into force.

The PPS analysis methodology named “Design and Evaluation Process Outline, DEPO” is the design and evaluation process for PPS that starts with determining objectives, then designing a system to meet the objectives, and ends with an evaluation of PPS effectiveness to verify that the system performs well compared to the objectives [2]. So far, some methods for the evaluation of PPS effectiveness have been proposed. The basic established analysis method used in the DEPO was “Estimate of Adversary Sequence Interruption, EASI” approach that was developed by Sandia National Laboratory (SNL) in the 1970s [3].

In the 1980s, SNL developed another method called “Systematic Analysis of Vulnerability to Intrusion, SAVI” which was on the basis of the EASI approach for the evaluation of multi-path in PPS [4]. If the detailed data of the threat, target, facility, site-specific PPS elements, and the response force time is confirmed, the 10 most vulnerable paths can be calculated by the SAVI platform. Later, for the analysis of the threat from insiders and outsiders, a comprehensive method named “Analytic System and Software for Evaluating Safeguards and Security, ASSESS” was developed by the Department of Energy (DOE) [5].

The aforementioned evaluative methods and software tools were only used in the one-dimensional model. The researchers of Korea Institute of Nuclear Non-proliferation and Control presented a novel method named “Systematic Analysis of Physical Protection Effectiveness, SAPE” which can be used in two-dimensional models [6].

In previous work, an integrated platform for analysis and design (IPAD) was proposed to evaluate the PPS effectiveness in three-dimensional models [7]. By combining the functions of three-dimension modeling of PPS with two-dimension drawing (such as CAD drawings) generation, IPAD provides designers with comprehensive and visualized information of PPS in one platform and enables a quick and convenient design of PPS. However, IPAD adopts EASI approach as the basic theoretical analysis method to analyze the PPS effectiveness. Moreover, IPAD applies a heuristic approach (HAPPS) [8] for the evaluation of Physical Protection System Effectiveness, which is combined EASI approach and Ant Colony Optimization (ACO) algorithm. If the assignment of parameters are not appropriate, ACO algorithm as a heuristic algorithm is easy to cause the results do not convergence, local optimum, and time-consuming.

In this paper, a modified method is presented on the basis of SAPE and EASI approaches. In the PPS, the evaluation of vulnerable path can come down to path-planning. Different design basis threat (DBT) signify different intrusion path. SAPE method uses A* algorithm as heuristic path-finding approach to evaluate the PPS effectiveness.

Different from the SAPE method, a novel and comprehensive method named “Heuristic Path-finding for the Evaluation of PPS effectiveness, HPEP” presents another intrusion mode. Heuristic information only considers detection probability. In this paper, contrastive analysis of the value of the heuristic information will help analysts to select the best way. Using A* algorithm for path-finding will not seek the most vulnerable intrusion path if heuristic information is considered. However, for non-heuristic information, A* algorithm will be equivalent to the Dijkstra algorithm [9] that can seek the most vulnerable intrusion path which is described in detail.

Hypothetically, HPEP method only considers an adversary intruding the NPPs and the basic function of PPS is to protect NPPs. If a group of adversaries intrude NPPs, the response forces have a main responsibility to interrupt the intrusion actions when the PPS detects the adversaries. This paper assumes that insiders only provide intrusion of convenience such as some sensors fail to detect and the delay devices are out of action. Also, the primary targets in this paper are assumed as physical assets, electronic data, or anything that could impact the critical facilities operations. The secondary targets are some PPS components, defense devices, detection devices, or others can reduce the PPS effectiveness [1].

The simulation model for the path-finding of PPS will be briefly introduced. HPEP method includes three path-finding modes. It uses detection probability and interruption probability as heuristic functions to seek the vulnerable intrusion path and takes the response force time as heuristic information to find the shortest path for the response force reaching the target in time. This is discussed in detail. Moreover, three simulation experiments study on the PPS evaluation will be presented.

Section snippets

Simulation modeling

In this paper, take Autodesk Computer Aided Design (AutoCAD) as a preliminary model tool for the design drawings of PPS. This is the common method used in NPPs and has been used in the previous work. It is convenient to interactively invoke CAD drawings [10] and identify the controls (equipment) of the models for the evaluation of PPS effectiveness. During the PPS design stage, designers by means of CAD secondary development, transfer equipment data as extended data stored in each equipment,

Basic A* algorithm for path-finding

The HPEP method adopts heuristic path-finding algorithm to reduce the computer resource in a large two-dimensional model. When a virtual character moves from the current position to the next position, the HPEP method can judge its actions such as where it leaves and where it will reach, and calculate a rough path. It then refines the rough path in each region.

A* algorithm is applied in a static grid for path planning. Compared with other path-finding algorithm, the A* algorithm has high search

Simulation experiments for the feasible analysis of HPEP method

In this paper, according to the different levels of DBT needed to conduct two experiments, the first experiment considers the low level of DBT (such as outsiders who do not know the detailed information of NPPs) and evaluates the lowest detection probability of the adversary intrusion path; the second experiment considers the high level of DBT which may be colluded with insiders and evaluates the lowest interruption probability like the experiment one. The Insider is defined as anyone who has

Conclusion

The experimental results confirm that the HPEP method for the evaluation of PPS effectiveness is available and successful. For HPEP method, it will be time-consuming to seek an accurate vulnerable adversary path when using non-heuristic information, or time-saving to calculate a relative vulnerable adversary path when using appropriate heuristic information. HPEP has rapid searching capability which is a requirement for some engineering applications such as virtual reality training.

The current

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