In the next years, drones will be part of our daily lives composing a parallel environment “over our heads,” having a dynamic traffic flow. The Internet of Drones (IoD) defines a robust and reliable distributed mobile network to manage and provide fair navigation and communication to drones. In this envisioned network environment, location privacy will be a paramount requirement to protect aerial and grounded devices. There is a lack of studies that investigate location privacy in the IoD. Our previous work was the first to propose a Location Privacy Protection Mechanism (LPPM) for IoD to the best of our knowledge. However, this mechanism does not consider the dynamics of the IoD traffic flow, hindering its performance. Hence, in this study, we present BioMixD, a bio-inspired and traffic-aware Mix Zone placement strategy for location privacy on the IoD. We integrate this strategy with our previous solution, leveraging an enhanced LPPM named t-MixDrones. We conducted an extensive experimental evaluation, investigating a wide range of IoD scenarios, and compared t-MixDrones with other mechanisms. The results highlighted that t-MixDrones overcomes the mechanisms in all scenarios, providing a better location privacy level, mainly drone coverage, and anonymization rate. Hence, we advance the state-of-the-art of LPPMs for the IoD environment.
Svaigen, A. R., Boukerche, A., Ruiz, L. B., & Loureiro, A. A. (2022). BioMixD: A bio-inspired and traffic-aware mix zone placement strategy for location privacy on the internet of drones. Computer Communications, 195, 111-123.