Evidence map›Paper›PMID 36298191›Full record

ArticleSensors (Basel, Switzerland)2022

Distributed Supervision Model for Enterprise Data Asset Trading Based on Blockchain Multi-Channel in Industry Alliance.

Jianxiong Zhang, Bing Guo, Xuefeng Ding, Dasha Hu, Yuming Jiang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jianxiong ZhangCollege of Computer Science, Sichuan University, Chengdu 610065, China.
Bing GuoCollege of Computer Science, Sichuan University, Chengdu 610065, China.
Xuefeng DingCollege of Computer Science, Sichuan University, Chengdu 610065, China.
Dasha HuCollege of Computer Science, Sichuan University, Chengdu 610065, China.
Yuming JiangCollege of Computer Science, Sichuan University, Chengdu 610065, China.

Funding

National Key R&D Program of China 2020YFB1707900 and 2020YFB1711800National Natural Science Foundation of China 62172061the Science and Technology Project of Sichuan Province 2022YFG0159, 2022YFG0155, 2022YFG0157, 2021GFW019, 2021YFG0152, 2021YFG0025, 2020YFG0322
6 · The paper itself

Abstract

Compared with traditional physical commodities, data are intangible and easy to leak, and the related trading process has problems, such as complex participating roles, lengthy information flow, poor supervisory coverage and difficult information traceability. To handle these problems, we construct a distributed supervision model for data trading based on blockchain, and conduct multi-party hierarchical and multi-dimensional supervision of the whole process of data trading through collaborative supervision before the event, at present and after the event. First, the characteristics of information flow in the data trading process are analyzed, and the main subject and key supervision information in the data trading process are sorted out and refined. Secondly, combined with the actual business process of data trading supervision, a multi-channel structure of distributed supervision is proposed by adopting an access-verification-traceability strategy. Finally, under the logical framework of the supervision model, the on-chain hierarchical structure and the data hybrid storage method of "on-chain + off-chain" are designed, and multi-supervisor-oriented hierarchical supervision and post-event traceability are realized through smart contracts. The results show that the constructed blockchain-based distributed supervision model of data trading can effectively isolate and protect sensitive and private information between data trading, so as to realize the whole process, multi-subject and differentiated supervision of key information of data trading, and provide an effective and feasible method for the controllable and safe supervision of data trading.

Indexed as

BlockchainCommerceIndustryInformation Storage and Retrievalblockchaindata assetdata tradingdistributed supervisionmulti-channel

Identifiers

PMID36298191
PMCPMC9606958

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.