Privacy Preserving Path Planning in an Adversarial Zone
Iman Vakilinia, Mohammad Jafari, Deepak K. Tosh, Shahin Vakilinia · 2020
Using Unmanned Aerial Vehicles (UAVs) for package delivery is an emerging technology. This technology facilitates delivery by providing safety, speed, road flexibility, reducing road congestion, etc. However, as the UAVs' path can be monitored by the public, such delivery could pose serious privacy issues. This is due to the fact that an attacker can monitor UAVs' path toward a destination and passively infer sensitive information about the users or even actively interfere in a package delivery system. To address this problem, in this paper, we study the challenges of preserving the privacy of a UAV's destination in an adversarial zone. We propose a set of path planning algorithms to protect the UAV's destination from a curious adversary. Our model does not rely on security by obscurity, which means that we assume the path planning algorithm is known to the public including adversary.