Analyzing the UAVs Traffic Flow to Enhance the Drone's Anonymization on the Internet of Drones
Artigo publicado em
Resumo
The Internet of Drones (IoD) is a novel mobile network paradigm with particular aspects, demanding security and privacy requirements. Mix Zones (MZ) is a location privacy protection mechanism in traditional mobile networks focusing on anonymizing a node's identity. In this regard, Mix Zone Placement (MZP) is a current challenge related to the design of MZ in IoD. As occur in terrestrial mobile environments, analyzing the vehicles' traffic flow can lead to enhanced strategies to solve MZP. This study conducts the first technical analysis of the MZP in this paradigm. We investigate three MZP strategies: an empirical MZP, a strategy based on visitation frequency, and an Ant-Colony Optimization (ACO) method. Our results reveal a deep relation between the drone's traffic flow and the MZP. Moreover, the ACO method is suitable for deployment in a location privacy protection mechanism, overcoming other strategies regarding location privacy, diversity, and efficiency.URL de Acesso
https://dl.acm.org/doi/abs/10.1145/3551662.3561198Informações Adicionais
Alisson R. Svaigen, Azzedine Boukerche, Linnyer B. Ruiz, and Antonio A. F. Loureiro. 2022. Analyzing the UAVs Traffic Flow to Enhance the Drone's Anonymization on the Internet of Drones. In Proceedings of the 12th ACM International Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications (DIVANet '22). Association for Computing Machinery, New York, NY, USA, 45–52. https://doi.org/10.1145/3551662.3561198