A Hypothesis Testing-based Framework for Cyber Deception with Sludging

In this paper, we present a novel hypothesis testing framework to model an attacker's decision-making during the reconnaissance phase and employ the framework to design strategic deception strategies that can provide the attacker with optimally falsified information structures. We characterize the criterion for such structures to “blind” the attacker, i.e., to completely confuse it, as well as the optimal falsification strategy when the attacker cannot be blinded. We also characterize optimal information acquisition costs that can be imposed on the attacker to maximally “sludge” its decision-making process during the reconnaissance phase. Numerical results have been presented to gain important insights into the developed strategies.