  Adversarial reconnaissance is a crucial step in sophisticated cyber-attacks
as it enables threat actors to find the weakest points of otherwise
well-defended systems. To thwart reconnaissance, defenders can employ cyber
deception techniques, such as deploying honeypots. In recent years, researchers
have made great strides in developing game-theoretic models to find optimal
deception strategies. However, most of these game-theoretic models build on
relatively simple models of adversarial reconnaissance -- even though
reconnaissance should be a focus point as the very purpose of deception is to
thwart reconnaissance. In this paper, we first discuss effective cyber
reconnaissance mitigation techniques including deception strategies and beyond.
Then we provide a review of the literature on deception games from the
perspective of modeling adversarial reconnaissance, highlighting key aspects of
reconnaissance that have not been adequately captured in prior work. We then
describe a probability-theory based model of the adversaries' belief formation
and illustrate using numerical examples that this model can capture key aspects
of adversarial reconnaissance. We believe that our review and belief model can
serve as a stepping stone for developing more realistic and practical deception
games.
