Application of social network theory to prioritizing Oil & Gas industries protection in a networked critical infrastructure system

Abstract As a typical process industry, the Oil & Gas industries play a key role within a networked critical infrastructure system in terms of their interconnection and interdependency. While the tight coupling of infrastructures increases the efficiency of infrastructure operations, interdependency between infrastructures may cause cascading failure of infrastructures. The interdependency between critical infrastructures gives rise to an infrastructure network. In this paper, we apply social network analysis, an analytical tool used by social scientists, to study human interactions and to analyze characteristics of the critical infrastructure network. We identify Oil & Gas, Information & Communication Technologies (ICT), and Electricity as three infrastructures that are most relied upon by other infrastructures, thus these may cause the greatest cascading failure of the infrastructures. Among the three, we further determine that Oil & Gas and Electricity are the more vulnerable infrastructures. As a result, priority toward critical infrastructure protection should be given to the Oil & Gas and Electricity infrastructures since they are most relied upon but at the same time depend more on other infrastructures.

[1]  Daniel S. Kirschen,et al.  Criticality in a cascading failure blackout model , 2006 .

[2]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994 .

[3]  Adilson E Motter,et al.  Cascade-based attacks on complex networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[4]  L. Comfort,et al.  Coordination in Rapidly Evolving Disaster Response Systems , 2004 .

[5]  Kim J. Vicente,et al.  Sociotechnical systems, risk management, and public health: comparing the North Battleford and Walkerton outbreaks , 2003, Reliab. Eng. Syst. Saf..

[6]  Richard G. Little A socio-technical systems approach to understanding and enhancing the reliability of interdependent infrastructure systems , 2004 .

[7]  W. Li,et al.  An expert system for an emergency response management in Networked Safe Service Systems , 2011, Expert Syst. Appl..

[8]  Rae Zimmerman Decision-making and the vulnerability of interdependent critical infrastructure , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[9]  John Scott Social Network Analysis , 1988 .

[10]  Alice Hills,et al.  Insidious Environments: Creeping Dependencies and Urban Vulnerabilities , 2005 .

[11]  James P. Peerenboom,et al.  Identifying, understanding, and analyzing critical infrastructure interdependencies , 2001 .

[12]  Vicki M. Bier,et al.  Balancing Terrorism and Natural Disasters - Defensive Strategy with Endogenous Attacker Effort , 2007, Oper. Res..

[13]  T. M. Wood,et al.  An infrastructure vulnerability assessment methodology for metropolitan areas , 2002, Proceedings. 36th Annual 2002 International Carnahan Conference on Security Technology.

[14]  Hüseyin Uzunalioglu,et al.  A network survivability model for critical national infrastructures , 2004, Bell Labs Technical Journal.

[15]  George E. Apostolakis,et al.  Identification of critical locations across multiple infrastructures for terrorist actions , 2007, Reliab. Eng. Syst. Saf..

[16]  George E Apostolakis,et al.  A Screening Methodology for the Identification and Ranking of Infrastructure Vulnerabilities Due to Terrorism , 2005, Risk analysis : an official publication of the Society for Risk Analysis.

[17]  Benoit Robert A method for the study of cascading effects within lifeline networks , 2004, Int. J. Crit. Infrastructures.

[18]  Wu Jun,et al.  Finding the most vital node by node contraction in communication networks , 2005, Proceedings. 2005 International Conference on Communications, Circuits and Systems, 2005..

[19]  D. McEntire Triggering agents, vulnerabilities and disaster reduction: towards a holistic paradigm , 2001 .