Game-theoretic models are a convenient tool to systematically analyze competitive\nsituations. This makes them particularly handy in the field of security where a company or a critical\ninfrastructure wants to defend against an attacker. When the optimal solution of the security game\ninvolves several pure strategies (i.e., the equilibrium is mixed), this may induce additional costs.\nMinimizing these costs can be done simultaneously with the original goal of minimizing the damage\ndue to the attack. Existing models assume that the attacker instantly knows the action chosen by\nthe defender (i.e., the pure strategy he is playing in the i-th round) but in real situations this may\ntake some time. Such adversarial inertia can be exploited to gain security and save cost. To this end,\nwe introduce the concept of information delay, which is defined as the time it takes an attacker to\nmount an attack. In this period it is assumed that the adversary has no information about the present\nstate of the system, but only knows the last state before commencing the attack. Based on a Markov\nchain model we construct strategy policies that are cheaper in terms of maintenance (switching costs)\nwhen compared to classical approaches. The proposed approach yields slightly larger security risk\nbut overall ensures a better performance. Furthermore, by reinvesting the saved costs in additional\nsecurity measures it is possible to obtain even more security at the same overall cost
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