Private UAV-Assisted IoT Data Collection: An Energy-Privacy Trade-off

• Main Authors: Fenelon, Benjamin, Enayati, Saeede, Pishro-Nik, Hossein
• Format: Conference Proceeding
• Language: English
• Subjects: Autonomous aerial vehicles; Data collection; Differential Privacy; Energy consumption; IoT Data Collection; Location Privacy; Performance evaluation; Power supplies; Privacy; UAV; Upper bound
• ISSN: 2643-4202
• DOI: 10.1109/PST58708.2023.10320196

Unmanned aerial vehicles (UAVs) offer intriguing possibilities for Internet of Things (IoT) data collection. However, it can also jeopardize the privacy of IoT devices. In particular, an adversary can deduce the location of IoTs by monitoring the UAV's mobility patterns, which necessitates the analysis of privacy-preserving mechanisms that protect IoT location privacy. Nonetheless, integrating privacy measures into operations incurs additional expenses. One of these costs is the added distance that UAVs may need to travel to accomplish their task, in turn increasing energy consumption. This paper investigates the trade-off between privacy and energy in the UAV-assisted IoT data collection application. First, we consider a preliminary privacy mechanism and analytically obtain the upper bounds of the extra flight distance and energy consumption for the UAV. Then, we consider a location-based differential privacy mechanism to achieve geo-indistinguishability. As expected, our study shows that imposing privacy constraints on UAV-assisted IoT data collection leads to increased UAV energy consumption. Specifically, as privacy guarantees become more restrictive, the energy consumption of UAVs increases exponentially. Nevertheless, given an energy constraint, one can assure a certain level of privacy guarantee.