In the era of digital economies, data has emerged as a critical production factor, driving innovation and economic growth. Governments worldwide have implemented policies and frameworks to facilitate data circulation while ensuring privacy protection. Data trading systems play a crucial role in data circulation. However, existing centralized data trading systems face significant challenges, including trust deficits, transparency issues, and vulnerability to data breaches. To address these critical issues, this paper presents TDTS (Trusted Data Trading System), an innovative blockchain-based framework that integrates data identification and private information retrieval mechanisms. Our system architecture leverages three fundamental technologies: blockchain smart contracts for transaction automation, decentralized data identification for provenance verification, and private information retrieval (PIR) techniques for pre-trading data verification. This comprehensive approach establishes a robust pipeline for data flow management, which includes data identification, upload, browsing, and trusted transaction, thereby ensuring secure and verifiable data circulation within a decentralized ecosystem. The implementation utilizes Hyperledger Fabric to construct a consortium blockchain network, specifically designed for data entities engaged in trading activities. We introduce two novel pre-trading verification schemes based on PIR techniques: (1) a randomized data verification format retrieval mechanism, and (2) a multi-query data authenticity verification protocol. Through the implementation of a fully functional TDTS prototype, we conduct extensive performance evaluations and practical assessments, demonstrating the system’s effectiveness and efficiency in addressing trust and security concerns in decentralized data trading environments.