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Motivated by the problem of optimal security resource deployment in critical infrastructure systems, we study a non-zero-sum security game over the substations of a power system in which the player payoffs depend upon the maturity of the security resources at each substation according to NERCCIP standards. Extending previous work, we give a structural characterization of the possible types of Nash equilibria in our non-zero-sum additive security game model, present feasibility conditions for equilibria of each type, and propose a novel algorithm to compute an equilibrium. Utilizing our characterization of the possible equilibria in additive security games, we propose a method to obtain a suboptimal solution to the problem of maximizing the expected outcome to the system operator by varying the maturity of security resources deployed at each substation and demonstrate the method by simulation. 

The increasing penetration of cyber systems into smart grids has resulted in these grids being more vulnerable to cyber physical attacks. The central challenge of higher order cyber-physical contingency analysis is the exponential blow-up of the attack surface due to a large number of attack vectors. This gives rise to computational challenges in devising efficient attack mitigation strategies. However, a system operator can leverage private information about the underlying network to maintain a strategic advantage over an adversary equipped with superior computational capability and situational awareness. In this work, we examine the following scenario: A malicious entity intrudes the cyber-layer of a power network and trips the transmission lines. The objective of the system operator is to deploy security measures in the cyber-layer to minimize the impact of such attacks. Due to budget constraints, the attacker and the system operator have limits on the maximum number of transmission lines they can attack or defend. We model this adversarial interaction as a resource-constrained attacker-defender game. The computational intractability of solving large security games is well known. However, we exploit the approximately modular behavior of an impact metric known as the disturbance value to arrive at a linear-time algorithm for computing an optimal defense strategy. We validate the efficacy of the proposed strategy against attackers of various capabilities and provide an algorithm for a real-time implementation.