Efficient Deduplicated Reporting in Fog-Assisted Vehicular Crowdsensing

In this paper, we propose an efficient deduplicated reporting scheme in fog-assisted vehicular crowdsensing. Based on a certificateless aggregate signcryption scheme (CLASC), the proposed scheme provides a promising approach for improving storage and communication overhead while maintaining content privacy. Specifically, roadside units (RSUs) as fog nodes are able to detect and remove any replicate crowdsensing reports without accessing information about their contents. Furthermore, the proposed scheme achieves fairness between vehicles whose reports are reduplicated and deleted. The scheme is designed with security properties, including report confidentiality, integrity, mutual authenticity, privacy, anonymity, secure data deduplication and key escrow resilience. To conclude, we elaborate on the achievement of secure data deduplication property and demonstrate the efficiency of the low computational and communication overhead of the proposed scheme.