Optimization of Cybersecurity Investment Strategies in the Smart Grid Using Game-Theory

With the increasing penetration of cyber systems in the power grid, it is becoming increasingly imperative to deploy adequate security measures all across the grid to secure it against any kind of cyber threat. Since financial resources for investment in security are limited, optimal allocation of these cybersecurity resources in the grid is extremely important. At the same time, optimization of these investments proves to be challenging due to the uncertain behavior of attackers and the dynamically changing threat landscape. Existing solutions for this problem either do not address the dynamic behavior of adversaries or lack in the practical feasibility of the defense models. This paper addresses the problem of optimizing investment strategies in the cybersecurity infrastructure of a smart grid using a game-theoretic approach. The attacker is modeled using various attacker profiles which represent the possible types of adversaries in the context of CPS. Each profile has certain characteristics to bring out the aspect of uncertain behavior of the adversaries. The defender is modeled with various pragmatic characteristics that can be easily translated to the real-world grid scenarios for implementation. These characteristics include the standards laid down by the North American Electric Reliability Corporation (NERC) for Critical Infrastructure Protection (CIP) commonly known as the NERC-CIP standards. The game-theoretic framework allows us to obtain optimal strategies that the defender of the grid can adopt to minimize its losses against the possible attack threats on the grid. The concept is illustrated by a simplistic 3-bus power system model case study which depicts how the solution can be translated to practical implementation in the actual grid.