  In this paper, a novel mathematical framework is introduced for modeling and
analyzing the cyber-physical security of time-critical UAV applications. A
general UAV security network interdiction game is formulated to model
interactions between a UAV operator and an interdictor, each of which can be
benign or malicious. In this game, the interdictor chooses the optimal
location(s) from which to target the drone system by interdicting the potential
paths of the UAVs. Meanwhile, the UAV operator responds by finding an optimal
path selection policy that enables its UAVs to evade attacks and minimize their
mission completion time. New notions from cumulative prospect theory (PT) are
incorporated into the game to capture the operator's and interdictor's
subjective valuations of mission completion times and perceptions of the risk
levels facing the UAVs. The equilibrium of the game, with and without PT, is
then analytically characterized and studied. Novel algorithms are then proposed
to reach the game's equilibria under both PT and classical game theory.
Simulation results show the properties of the equilibrium for both the rational
and PT cases. The results show that the operator's and interdictor's bounded
rationality is more likely to be disadvantageous to the UAV operator.
