UDiPP: A Framework for Differential Privacy Preserving Movements of Unmanned Aerial Vehicles in Smart Cities

Thanks to recent enormous advance of mobile and vehicular technology, it is highly expected that unmanned aerial vehicles (UAVs) are used for various applications in smart cities as well as the number of flying UAVs in the sky is increasing explosively. However, such a proliferation of UAVs accompanies additional critical issues to be considered for efficient, secure use of UAVs. One of important issues should be the privacy of people. When the UAVs fly to perform specific objectives, minimizing movements of UAVs is an important issue to minimize mission completion time and to maximize the network lifetime of UAVs. To do so, one intuitive solution is that UAVs may pass through private area of citizens whereas people do not want any penetration into own area without a permission. For those situations, we may take into account a compromise so that people can decide whether they give a differential, temporal permission for each UAV to access their areas depending on specific benefits by use of UAVs or emergent situation for public safety. In this study, we introduce a framework for privacy preserving movements of UAVs with differential UAVs' permissions given by citizens, which is called as UAVs' differential privacy preserving movements (UDiPP). Then, using integer linear programming, we formally define a problem whose objective is to minimize total movements of UAVs with preserving privacy of citizens. To solve the problem, we propose a novel approach with a creation of UDiPP graph and then evaluate its performance through extensive simulations.