Blockchain-enabled scalable data trading with secure traceability in edge environments

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Abstract

In the era of the digital economy and pervasive Internet of Things (IoT) connectivity, massive volumes of data are generated in the edge environments such as from smart sensors, industrial equipment, and mobile devices. Traditional centralized data trading platforms struggle with latency, privacy leakage, and inefficient resource utilization in mobile and distributed environments. To address these issues, this paper proposes a blockchain-powered edge-oriented data trading framework optimized for secure and low-latency transactions in IoT and mobile edge computing scenarios. We introduce a lightweight, multi-threaded data export mechanism tailored for constrained edge nodes, significantly improving data throughput while reducing transmission delay. A blind text watermarking scheme is deployed to enhance data traceability and resist unauthorized distribution. Data fragmentation combined with Merkle tree integrity verification and recoverable transfer protocols ensures robust and verifiable communication, even under intermittent connectivity. To strengthen trust and auditability, a blockchain-based authentication layer records cryptographic proofs of data ownership and transaction signatures in a tamper-resistant and transparent ledger. Experimental evaluations demonstrate enhanced system responsiveness and scalability under edge computing constraints. Security analyses confirm the framework’s resilience against concurrency conflicts, data tampering, and unauthorized access. By integrating blockchain, edge computing, and privacy-preserving techniques, this work lays the groundwork for secure, decentralized, and efficient data trading infrastructures, particularly suited to next-generation IoT ecosystems and mobile computing environments.

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APA

Mi, B., Mo, W., Hu, Z., & Deng, M. (2026). Blockchain-enabled scalable data trading with secure traceability in edge environments. Journal on Wireless Communications and Networking, 2026(1). https://doi.org/10.1186/s13638-025-02565-7

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