Give Me a Secure Ride: TEE-Blockchain Enabled Privacy-Aware and Verifiable Ride Sharing Services

The proliferation of mobile internet and sharing economy has catalyzed the emergence of Ride-Sharing Services (RSSs) as a paradigm of spatial crowdsourcing in intelligent transportation. Compared with ride-hailing, RSSs present heightened challenges in security and service quality management due to bidirectional disclosure of trip plans and complex matching logic. Existing secure RSS solutions predominantly operate under semi-honest threat models or suffer from prohibitive computational complexity in service composition. However, ensuring public verifiability of matching outcomes is equally critical to prevent manipulation and ensure accountability in decentralized environments. Moreover, achieving a harmonious trade-off among privacy preservation, public verifiability, and matching efficiency remains an open challenge in RSS systems. This work proposes TBRS, a novel TEE-Blockchain powered privacy-aware Ride-Sharing framework, which innovatively addresses three core challenges in service computing: (1) formalizing an inclusive matching model that extends traditional identical matching through trajectory region overlap analysis and direction alignment verification; (2) designing an Index-Preserving Bloom Filter (IP-BF) coupled with Hilbert R-tree spatial indexing, achieving O(log n) matching complexity through computational geometry optimization; (3) implementing a hybrid trusted execution environment via SGX-enhanced consortium blockchain with private smart contracts, ensuring verifiable service operations management under malicious threats. The framework demonstrates significant advancements in service performance management through systematic experiments: 2× ∼ 11× acceleration in on-chain service composition, 6× ∼ 33× improvement in off-chain computation efficiency, while maintaining over 99% service matching accuracy.These results signify that TBRS effectively breaks the efficiency bottleneck of existing privacy-preserving RSS solutions, making decentralized ride-sharing practical for deployment.