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An adversarial model for attack vector vulnerability analysis on power and gas delivery operations

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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 continuoustime 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.

Author(s):

Ignacio Losada Carreno    
Arizona State University
United States

Anna Scaglione    
Arizona State University
United States

Anatoly Zlotnik    
Los Alamos National Laboratory
United States

Deepjyoti Deka    
Los Alamos National Laboratory
United States

Kaarthik Sundar    
Los Alamos National Laboratory
United States

 

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