Privacy-preserving control of video transmissions for drone-based intelligent transportation systems

Abstract

The drones are now frequently used for many smart city applications including intelligent transportation to provide situational awareness for drivers as well as other stakeholders that manage the traffic. In such situations one of the widely collected data is video that is recorded by a drone and streamed in real-time to a remote control center. The data can then be accessed through cloud services to do further analysis and take actions. However, this captured video may contain private information from the passing by citizens and allow recognition and tracking if it is intercepted by malicious users. While the video data can be stored as encrypted in the cloud, this still does not address the privacy problem as the third party providers still need to decrypt the data to perform any further processing. To address this issue, we propose using fully homomorphic encryption (FHE) which will not only provide confidentiality of the data but also enable processing on the encrypted video data by cloud providers and other third parties without exposing any privacy. However, since fully homomorphic systems have a lot of overhead, in this paper, we propose to conduct background extraction on video images and transmit only the changing foreground to minimize data transmission. As we use FHE, this allows reconstruction of the video at the server without decrypting the data. We tested the feasibility of the proposed approach extensively under various conditions including the type of FHE used, the underlying communication protocols and video size. The results indicate that our approach can even outperform AES-based method in terms of total time to complete the video transmission while additionally enabling privacy features.