An Adversarial Model for Attack Vector Vulnerability Analysis on Power and Gas Delivery Operations

TL;DR

This paper introduces a model to quantify the impact of cyber-attacks on power and gas delivery systems, integrating operationally realistic models and Monte Carlo simulations to assess reliability and operational costs.

Contribution

It presents a novel continuous-time Markov chain model for cyber-attack vector analysis on power and gas infrastructure, linking cyber incidents to operational impacts.

Findings

Model effectively quantifies cyber-attack impacts on system reliability.

Monte Carlo simulations estimate increased operational costs.

Case study demonstrates practical application of the model.

Abstract

Power systems often rely on natural gas pipeline networks to supply fuel for gas-fired generation. Market inefficiencies and a lack of formal coordination between the wholesale power and gas delivery infrastructures may magnify the broader impact of a cyber-attack on a natural gas pipeline. In this study we present a model that can be used to quantify the impact of cyber-attacks on electricity and gas delivery operations. We model activation of cyber-attack vectors that attempt to gain access to pipeline gas compressor controls using a continuous-time Markov chain over a state space based on the gas operator Industrial Control System firewall zone partition. Our approach evaluates the operating states and decision-making in the networks using physically realistic and operationally representative models. We summarize these models, the sequence of analyses used to quantify the impacts of a cyber-incident, and propose a Monte Carlo simulation approach to quantify the resulting effect on the reliability of the bulk power system by the increase in operational cost. The methodology is applied to a case study of interacting power, gas, and cyber test networks.