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access icon openaccess Developing correlation indices to identify coordinated cyber-attacks on power grids

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 29/03/2018, Accepted 11/10/2018, Revised 15/09/2018, Published 15/10/2018

Increasing reliance on Information and Communication Technology exposes the power grid to cyber-attacks. In particular, Coordinated Cyber-Attacks (CCAs) are considered highly threatening and difficult to defend against, because they (i) possess higher disruptiveness by integrating greater resources from multiple attack entities, and (ii) present heterogeneous traits in cyber-space and the physical grid by hitting multiple targets to achieve the attack goal. Thus, and as opposed to independent attacks, whose severity is limited by the power grid's redundancy, CCAs could inflict disastrous consequences, such as blackouts. In this study, the authors propose a method to develop Correlation Indices to defend against CCAs on static control applications. These proposed indices relate the targets of CCAs with attack goals on the power grid. Compared to related works, the proposed indices present the benefits of deployment simplicity and are capable of detecting more sophisticated attacks, such as measurement attacks. The method is demonstrated using measurement attacks against Security Constrained Economic Dispatch.

Inspec keywords: power grids; power engineering computing; power generation dispatch; security of data; power generation economics; power system security

Other keywords: correlation indices; multiple attack entities; information and communication technology; attack goal; power grid; multiple targets; measurement attacks; CCAs; physical grid; security constrained economic dispatch; independent attacks; coordinated cyber-attacks; cyber-space; sophisticated attacks; static control applications; increasing reliance

Subjects: Data security; Power system management, operation and economics; Power engineering computing; Power system protection

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