Determination of the Most Interconnected Sections of Main Gas Pipelines Using the Maximum Clique Method

Abstract

This article is devoted to the definition of the most important combinations of objects in critical network infrastructures. This study was carried out using the example of the Russian gas transmission network. Since natural gas is widely used in the energy sector, the gas transmission network can be exposed to terrorist threats, and the actions of intruders can be directed at both gas fields and gas pipelines. A defender–attacker model was proposed to simulate attacks. In this model, the defender solves the maximum flow problem to satisfy the needs of gas consumers. By excluding gas pipelines, the attacker tries to minimize the maximum flow in the gas transmission network. Russian and European gas transmission networks are territorially very extensive and have a significant number of mutual intersections and redundant pipelines. Therefore, one of the approaches to inflicting maximum damage on the system is modeled as an attack on a clique. A clique in this study is several interconnected objects. The article presents the list of the most interconnected sections of main gas pipelines, the failure of which can cause the greatest damage to the system in the form of a gas shortage among consumers. Conclusions were drawn about the applicability of the maximum clique method for identifying the most important objects in network critical infrastructures.

Comparative efficiency of application of the maximum clique method in searching for critically important objects of the gas industry

“…Combinations of interconnected nodal compressor stations forming cliques were determined [27]. A total of 45 cliques were found, consisting of three elements.…”

The Maximum Clique Problem and Integer Programming Models, Their Modifications, Complexity and Implementation

“…In [6], a bottom-up clustering algorithm based on recursive collapsing of small cliques in a graph, applied to VLSI (Very-Large-Scale Integration) design, is proposed. An application from the gas industry is described in [7]. In [8], a graph-theoretic clique finding a method for comparative modelling of protein structures is presented.…”