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

Ignacio Losada Carreño, Anna Scaglione, Anatoly Zlotnik, Deepjyoti Deka, Kaarthik Sundar

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Article number106777
JournalElectric Power Systems Research
Volume189
DOIs
StatePublished - Dec 2020

Keywords

  • Continuous-time Markov chain
  • cyber-physical Systems
  • optimal power flow
  • Purdue model
  • transient gas flow

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'An adversarial model for attack vector vulnerability analysis on power and gas delivery operations'. Together they form a unique fingerprint.

  • Cite this