SecCDS: Secure Crowdsensing Data Sharing Scheme Supporting Aggregate Query

This paper presents SecCDS, a secure crowdsensing data sharing scheme that supports aggregate queries ensuring location privacy and hiding query patterns. In crowdsensing environment, how to balance the trade-off of the sensor data applicability and the leakage abuse of participants’ location is a critical issue needed to pay attention. Aim at this and to cater to the demands of real-world crowdsensing workloads, we deployed a 2-server collaboration architecture in SecCDS, which protects participants’ location and query privacy against arbitrary misbehavior by one of the servers. SecCDS incorporates a recently developed cryptographic tool–function secret sharing to allow a participant to secret-share real-time location in an obfuscated structure, without compromising the effectiveness of aggregate queries. The theoretical analysis demonstrates that SecCDS achieves correctness while satisfying adaptive \(\mathcal {L}\) -semantic security. The experimental evaluation with two servers demonstrates that SecCDS could conduct highly parallelizable aggregate queries which is efficient for diverse crowdsensing applications.