RTSense: Providing Reliable Trust-Based Crowdsensing Services in CVCC

CVCC has garnered significant attention in recent years as a special cloud computing platform capable of broadening network service provisioning in mobile computing. Vehicular crowdsensing is a prime candidate for CVCC applications as connected vehicles can provide tremendous sensing, computing, and storage resources. Truthfulness of sensing data is very important, as malicious vehicles may create inaccuracy in sensing results. In this work, we propose RTSense, which enables trust-based crowdsensing services in CVCC. The architecture divides the system into control and data planes, where the trust authority and service providers sit in the control plane, and vehicles and fogs exist in the data plane. We provide solutions for anonymous vehicle authentication, interactive filtering truth discovery, and trust management for reliable crowdsensing. The experimental analysis shows that RTSense can effectively segregate malicious and trustworthy vehicles. We also identify interesting future directions along with possible solutions.