How to protect a genuine target against an attacker trying to detect false targets

Usage of false targets has proven to be an effective way to enhance the survivability of a genuine target in a defender–attacker game. Time, as an important factor, however, is seldom taken into account in the existing game theoretic models. This paper studies the complex interplay between two players and analyzes the equilibrium strategies and payoffs under various situations. In particular, both players make a simultaneous move at certain time points. The attacker chooses to either learn or attack whereas the defender chooses to either strengthen the genuine target or deploy more false targets. If learning behavior is chosen, the state of the system changes and the game continues. If attacking behavior is chosen, the game ends with probabilistic payoffs. We carry out experiments and obtain the corresponding equilibrium results (i.e. the optimal number of false targets for the defender and the optimal attack time for the attacker) under different learning and contest intensities. It shows that under certain conditions (high attacker resource, low learning intensity) the defender benefits from deploying more false targets with greater probabilities, whereas the attacker benefits from learning fewer targets and attacking earlier with greater probabilities with low resource, or high learning intensity. The results shed light on making enhanced decisions in terms of defense and deception strategies.