The deployment of Drone-as-a-Service (DaaS) applications has been significantly impeded due to the privacy and trust issues. The objective of this project is to enhance the privacy compliance of drones in DaaS applications. Based on techniques including Trusted Execution Environment (TEE), homomorphic encryption and blockchain, privacy enforcement mechanisms and frameworks are designed and developed. These approaches enable trustworthy DaaS applications such as verifiable location tracking (AliDrone), confidential remote data collection and processing (SHE), efficient DaaS task management (UAVChain), etc.
- Liu, T., Hojjati, A., Bates, A., & Nahrstedt, K. (2018, July). Alidrone: Enabling trustworthy proof-of-alibi for commercial drone compliance. In 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS) (pp. 841-852). IEEE.
- Liu, T., Guo, H., Danilov, C., & Nahrstedt, K. (2020, December). A Privacy-preserving Data Collection and Processing Framework for Third-party UAV Services. In 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) (pp. 683-690). IEEE.
This project is supported in part by the Department of Energy under Award Number DE-OE0000780, and NSF CNS grants 16-57534, 17-50024, and 13-30491.