Publication
Abstract
As data increasingly becomes a key factor of production for artificial intelligence (AI), this paper proposes a blockchain-enabled, decentralized AI data-market framework. To address the long-standing problems of low transparency, high privacy risk, and misaligned incentives in traditional data trading, we design a layered hybrid consensus that combines Proof of Stake (PoS) with Practical Byzantine Fault Tolerance (PBFT), balancing economic security with sub-second finality. A token-based incentive model that weights data quality, volume, and staking risk is introduced to couple value discovery with the suppression of low-quality data. By combining symmetric encryption with proxy re-encryption, the framework allows data to be “usable yet invisible” while exposing a compliance interface for regulated auditability. A prototype deployed on 18 nodes achieves 4,750 tx · s⁻¹ throughput and 148 ms latency, with energy consumption far below Proof-of-Work (PoW) schemes—demonstrating performance, privacy, and ESG friendliness. This work provides a reproducible technical path and theoretical foundation for sustainable innovation in data-factor circulation and AI applications.
Keywords
Blockchain , Decentralized Data Marketplace , Artificial Intelligence , Layered Hybrid Consensus , Token Incentive , Data Privacy .
Metadata
Disciplines: Computer Science
Cite This Article
APA Style
Zhang, T. (2025). Constructing a decentralized ai data marketplace enabled by a blockchain-based incentive mechanism. Journal of Industrial Engineering and Applied Science, 3(3), 42-46. https://doi.org/10.70393/6a69656173.333032
Acknowledgments
The authors thank the editor and anonymous reviewers for their helpful comments and valuable suggestions.
FUNDING
INSTITUTIONAL REVIEW BOARD STATEMENT
DATA AVAILABILITY STATEMENT
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
INFORMED CONSENT STATEMENT
CONFLICT OF INTEREST
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
AUTHOR CONTRIBUTIONS
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