Privacy Protection for Internet of Drones: A Network Coding Approach - Chen, Yu-Jia; Wang, Li-Chun (IEEE internet of things journal, 2019)
This paper proposes an enhanced secure pseudonym scheme to protect the privacy of cloud data in Internet of Drones (IoD). Nowadays, drones equipped with cameras can provide surveillance and aerial photography applications. Unlike the video devices, personal drones with high mobility can track and follow an individual, causing both the identity and location privacy issues. However, IoD devices cannot implement complex cryptographic schemes because of limited computing power. To this end, we develop a secure light-weight network coding pseudonym scheme. Our designed two-tier network coding can decouple the stored IoD cloud data from the owner's pseudonyms. Therefore, our proposed network coding-based pseudonym scheme can simultaneously defend against both outside and inside attackers. We implement our proposed two-tier light-weight network coding mechanism when facing untrusted cloud database. Compared to the computationally secure hash-based pseudonym scheme, our proposed scheme achieves the highest unconditional security level, but also can reduce more than 90% of processing time as well as 10% of energy consumption.