Abstract
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.
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Notes
- 1.
Interested readers can read the security proof in Boyle et al.’s manuscript [10].
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Li, Y., Zhou, F., Xu, Z., Ji, D. (2024). SecCDS: Secure Crowdsensing Data Sharing Scheme Supporting Aggregate Query. In: Ge, C., Yung, M. (eds) Information Security and Cryptology. Inscrypt 2023. Lecture Notes in Computer Science, vol 14526. Springer, Singapore. https://doi.org/10.1007/978-981-97-0942-7_17
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DOI: https://doi.org/10.1007/978-981-97-0942-7_17
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