Abstract
Blockchain-based applications are becoming more and more widespread in business operations. This paper proposes a multi-source heterogeneous blockchain data quality assessment method for enterprise business activities, aiming at the problems that most of the data in enterprise business activities come from different data sources, information representation is inconsistent, information ambiguity between the same block chain is serious, and it is difficult to evaluate the consistency, credibility and value of information. The method realizes the consistency assessment by calculating the similarity of block information.After that, a trustworthiness characterisation method is proposed based on information sources and information comments, to obtain the trustworthiness assessment of the business. Finally, based on the information trustworthiness characterization, a value assessment method is introduced to assess the total value of business activity information in the blockchain, and a blockchain quality assessment model is constructed. The experimental results show that the proposed model has great advantages over existing methods in assessing inter-block consistency, intra-block activity information trustworthiness and the value of blockchain.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
He, X., Wang, J., Liu, J., et al.: Smart grid nontechnical loss detection based on power gateway consortium blockchain. Secur. Commun. Netw. 2021 (2021)
Shen, M., Sang, A.Q., Zhu, L.H., Sun, R.G., Zhang, C.: Recognition method of abnormal transaction behavior of blockchain digital currency based on motivation analysis. J. Comput. 44(01), 193–208 (2021)
Hong, S.: Research on sharding model for enabling cross heterogeneous blockchain transactions. J. Digit. Converg. 19(5), 315–320 (2021)
Fu, L.Q., Tian, H.B.: Ethereum voting protocol based on smart contract. J. Softw. 30(11), 3486–3502 (2019)
Wang, X.B., Yang, X.Y., Shu, X.F., Zhao, L.: Formal verification of smart contract for MSVL. J. Softw. 32(6), 1849–1866 (2021)
Truong, N., Lee, G.M., Sun, K., et al.: A blockchain-based trust system for decentralised applications: when trustless needs trust. Futur. Gener. Comput. Syst. 124, 68–79 (2021)
Lee, G.M.: A blockchain-based trust system for decentralised applications: when trustless needs trust. Future Gener. Comput. Syst. 124, 68–79 (2021)
Colomo-Palacios, R., Sánchez-Gordón, M., Arias-Aranda, D.: A critical review on blockchain assessment initiatives: a technology evolution viewpoint. J. Softw. Evol. Process 32(11), e2272 (2020)
Zhang, A., Zhong, R.Y., Farooque, M., et al.: Blockchain-based life cycle assessment: an implementation framework and system architecture. Resour. Conserv. Recycl. 152, 104512 (2020)
Yang, Y., Irsoy, O., Rahman, K.S.: Collective entity disambiguation with structured gradient tree boosting. arXiv preprint arXiv:1802.10229 (2018)
Xu, Y.L., Li, Z.H., Chen, Q., Wang, Y.Y., Fan, F.F.: Disambiguation method of inconsistent records based on factor graph. Comput. Res. Dev. 57(01), 175–187 (2020)
Yanling, F., et al.: Credibility assessment method of sensor data based on multi-source heterogeneous information fusion. Sensors 21(7), 2542 (2021)
Jain, P.K., Pamula, R., Ansari, S.: A supervised machine learning approach for the credibility assessment of user-generated content. Wireless Pers. Commun. 118(4), 2469–2485 (2021)
Moon, M.Y., Cho, H., Choi, K.K., et al.: Confidence-based reliability assessment considering limited numbers of both input and output test data. Struct. Multidiscip. Optim. 57(5), 2027–2043 (2018)
Lin, C., Zhang, M., Zhou, Z., et al.: A new quantitative method for risk assessment of water inrush in karst tunnels based on variable weight function and improved cloud model. Tunn. Undergr. Space Technol. 95, 103136 (2020)
Acknowledgement
This study was supported by the Applied Basic Research Program of Liaoning Province (No. 2022JH2/101300250); the Digital Liaoning Smart Building Strong Province (Direction of Digital Economy) (No. 13031307053000568); the National Key R&D Program of China (No. 2021YFF0901004); the Central Government Guides Local Science and Technology Development Foundation Project of Liaoning Province (No. 2022JH6/100100032); the Natural Science Foundation of Liaoning Province (No. 2022-KF-13-06).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Zhang, R., Li, S., Ding, J., Zhang, C., Du, L., Wang, J. (2023). Multi-source Heterogeneous Blockchain Data Quality Assessment Model. In: Yang, S., Islam, S. (eds) Web and Big Data. APWeb-WAIM 2022 International Workshops. APWeb-WAIM 2022. Communications in Computer and Information Science, vol 1784. Springer, Singapore. https://doi.org/10.1007/978-981-99-1354-1_9
Download citation
DOI: https://doi.org/10.1007/978-981-99-1354-1_9
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-1353-4
Online ISBN: 978-981-99-1354-1
eBook Packages: Computer ScienceComputer Science (R0)