Paper Info
Title
A Privacy-Preserving Data Collection and Processing Framework for Third-Party UAV Services
Abstract
Unmanned Aerial Vehicles (UAVs) are becoming more popular than ever in outdoor commercial services. Many third-party UAV companies offer their UAVs as mobile data collectors to assist their clients in remote data collection missions. However, due to the lack of trust and transparency, the clients often have very little control on the behavior of these UAVs. This issue is even exacerbated if the service had to deal with private client data. In this work, we propose a solution that enables third-party UAVs to collect and process private client data from remote data sites in a trustworthy and efficient manner. We design and implement the Secure Homomorphic Encryption (SHE) framework. SHE combines trusted hardware enclave and homomorphic encryption technologies to provide strong privacy primitives on client data. SHE features in a recrypt technique such that the computation and communication overhead for homomorphic encryption on the client data is minimized. In addition, SHE takes the advantage of UAVs' travelling time to run data aggregation tasks in order to speed-up data processing. Through laboratory experiments, we demonstrate that SHE can meet the performance requirement in many common data processing and aggregation missions. SHE thus can be introduced as a trustworthy framework for the third-party UAV service providers.
Year
DOI
Venue
2020
10.1109/TrustCom50675.2020.00095
2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
Keywords
DocType
ISSN
UAV, Data Collection and Processing, Homomorphic Encryption, TrustZone
Conference
2324-898X
ISBN
Citations 
PageRank 
978-1-6654-0393-1
0
0.34
References 
Authors
14
4
Name
Order
Citations
PageRank
Tianyuan Liu1124.03
Hongpeng Guo282.81
claudiu danilov352.25
Klara Nahrstedt47941636.63