A Fair and Trusted Trading Scheme for Medical Data Based on Smart Contracts
Source abstract
Abstract
Data is regarded as a valuable asset, and sharing data is a prerequisite for fully exploiting the value of data. However, the current medical data sharing scheme lacks a fair incentive mechanism, and the authenticity of data cannot be guaranteed, resulting in low enthusiasm of participants. A fair and trusted medical data trading scheme based on smart contracts is proposed, which aims to encourage participants to be honest and improve their enthusiasm for participation. The scheme uses zero-knowledge range proof for trusted verification, verifies the authenticity of the patient’s data and the specific attributes of the data before the transaction, and realizes privacy protection. At the same time, the game pricing strategy selects the best revenue strategy for all parties involved and realizes the fairness and incentive of the transaction price. The smart contract is used to complete the verification and game bargaining process, and the blockchain is used as a distributed ledger to record the medical data transaction process to prevent data tampering and transaction denial. Finally, by deploying smart contracts on the Ethereum test network and conducting experiments and theoretical calculations, it is proved that the transaction scheme achieves trusted verification and fair bargaining while ensuring privacy protection in a decentralized environment. The experimental results show that the model improves the credibility and fairness of medical data transactions, maximizes social benefits, encourages more patients and medical institutions to participate in the circulation of medical data, and more fully taps the potential value of medical data.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Blockchain Technology Applications and Security · Privacy-Preserving Technologies in Data · Retinal Imaging and Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (39)
Show source-provided references
1. Data as oil, infrastructure or asset? Three metaphors of data as economic value10.1108/JICES-04-2019-0044 ↗
2. Are patients electronically accessing their medical records? Evidence from national hospital data10.1377/hlthaff.2018.05437 ↗
3. Researchers at greenbone networks vulnerability analysis and management company discovered 400 million medical radiological images exposed online via unsecured pacs servers, 2019. https://securityaffairs.com/91452/hacking/pacs-servers-unprotected-online.html (accessed on 19/05/2023).
4. Unpatients—why patients should own their medical data10.1038/nbt.3340 ↗
5. Healthcare Medical Data Compliance Circulation Standards, 2023. http://www.cinsa.org.cn/2023/0901/c33219a517345/page.htm (accessed on 04/12/2023).
6. Electronic Health Records Market Size, Share, Growth Report, 2021. https://www.zionmarketresearch.com/report/electronic-health-records-market (accessed on 05/05/2023).
7. Enhancing traceability of infectious diseases: A blockchain-based approach10.1016/j.ipm.2021.102570 ↗
8. A fair protocol for data trading based on bitcoin transactions10.1016/j.future.2017.08.021 ↗
9. A systematic review of barriers to data sharing in public health10.1186/1471-2458-14-1144 ↗
10. A secure and privacy protection digital goods trading scheme in cloud computing
11. Fair offline digital content transaction system10.1049/iet-ifs.2010.0228 ↗
12. Provable fair document exchange protocol with transaction privacy for e-commerce10.3390/sym7020464 ↗
13. AccountTrade: Accountability against dishonest big data buyers and sellers10.1109/TIFS.2018.2848657 ↗
14. BDTF: A blockchain-based data trading framework with trusted execution environment
15. BDDT: Use blockchain to facilitate IoT data transactions10.1007/s10586-020-03119-w ↗
16. Toward a decentralized, trust-less marketplace for brokered IoT data trading using blockchain
17. Secure fair and efficient data trading without third party using blockchain
18. Modeling and analysis of data trading on blockchain-based market in IoT networks10.1109/JIOT.2021.3051923 ↗
19. Edge computing to secure IoT data ownership and trade with the Ethereum blockchain10.3390/s20143965 ↗
20. Informational cascade, regulatory focus, and purchase intention in online flash shopping10.1016/j.elerap.2023.101343 ↗
21. Fair-trading protocol for anonymised datasets requirements and solution
22. Machine learning based privacy-preserving fair data trading in big data market10.1016/j.ins.2018.11.028 ↗
23. CPchain: A copyright-preserving crowdsourcing data trading framework based on blockchain
24. Blockchain-based privacy-preserving fair data trading protocol
25. Secure, fair and instant data trading scheme based on bitcoin10.1016/j.jisa.2020.102511 ↗
26. Blockchain-based fair and fine-grained data trading with privacy preservation10.1109/TC.2023.3251846 ↗
27. A secure and efficient blockchain-based data trading approach for Internet of Vehicles10.1109/TVT.2019.2927533 ↗
28. A blockchain-based trading platform for big data
29. Blockchain-based data trading in edge-cloud computing environment10.1016/j.ipm.2021.102786 ↗
30. Optimal auction for effective energy management for UAV-assisted metaverse synchronization system
31. A multi-leader multi-follower stackelberg game for resource management in LTE unlicensed10.1109/TWC.2016.2623603 ↗
32. Game-theoretic resource pricing and provisioning strategies in cloud systems10.1109/TSC.2016.2633266 ↗
33. Mobile edge computing resource allocation: A joint Stackelberg game and matching strategy10.1177/1550147719861556 ↗
34. Healthchain: Secure EMRs management and trading in distributed healthcare service system10.1109/JIOT.2020.3038721 ↗
35. A peer-to-peer electronic cash system
36. Using blockchain technology to enhance the traceability of original achievements10.1109/TEM.2021.3066090 ↗
37. A next-generation smart contract and decentralized application platform
38. On the size of pairing-based non-interactive arguments
39. ZoKrates-scalable privacy-preserving off-chain computations