Parameterizing Moving Target Defenses

Moving Target Defense (MTD) is the concept of controlling change across multiple system dimensions, aiming to disrupt the adversary in the attack sequence for intrusion prevention. To date, there is a lack of progress in MTD modeling and evaluation to test the effectiveness of MTD techniques. In this paper we develop two analytical models based on closed-form solutions and Stochastic Petri Nets to analyze the effect of a dynamic platform technique based MTD on attack success rate. The numerical results from these two models agree with one another, providing cross-validation. Furthermore, the output of these models indicates the existence of parameter settings that decrease the security of the protected resource and settings that make MTD most effective in terms of minimizing the attack success probability.