Abstract
It is now paramount to protect critical infrastructures because of their significance for economic development and social well-being of modern societies. One of the main threats to these networked systems is from intentional attackers, who are resourceful and inventive in selecting time, target, and means of attack. Thus, attackers’ intelligence should be considered when developing intelligent and cost-effective protection strategies. In this research, critical infrastructures are modeled as networks and the development of network protection strategies is modeled as a two-stage game between a protector and an attacker with incomplete information. Due to the complexity of critical infrastructures, there are usually a large number of combinations of potential protection and attack strategies leading to a computational challenge to find the Pareto equilibrium solutions for the proposed game. To meet this challenge, this research develops an evolutionary algorithm to solve the proposed a transformation of the game into a multi-objective optimization model.
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