Abstract
The blockchain is a modern digital ledger that not only records currency transactions, but also records anything of value. Once the transaction is verified and submitted to the blockchain, it is difficult to recover. Therefore, in order to prevent malicious behavior, there should be a mechanism to evaluate the trust between participants before any transaction, which can effectively reduce the malicious behavior of malicious nodes. There are some nodes that provide low-quality services to quickly get rewards, and even malicious nodes may appear to deliberately provide extremely low-quality or invalid services. This paper proposes a blockchain-based trust mechanism for service nodes, which takes into account the privacy and security of the nodes, and is used to evaluate the confidence situation between the task assignment node and the task participating node. Experiments show that the mechanism we proposed can not only improve the service quality of service nodes, but also effectively distinguish high-quality nodes, low-quality nodes and malicious nodes, which provides an effective reference for selecting high-quality and credible service nodes.
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Acknowledgements
This work was supported by the Key Research and Development Program of Hainan Province (Grant No. ZDYF2020040), Major science and technology project of Hainan Province(Grant No. ZDKJ2020012), Hainan Provincial Natural Science Foundation of China (Grant Nos. 2019RC098) and National Natural Science Foundation of China (NSFC) (Grant No. 62162022, 62162024 and 61762033), Young Talents’ Science and Technology Innovation Project of Hainan Association for Science and Technology (Grant No. QCXM202007), Key project of College Students’ innovation and Entrepreneurship of Hainan University (Grant No. 20210110), Innovative scientific research project of Postgraduates in Colleges and universities in Hainan Province (Grant No. Hyb2020-01).
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Feng, W. et al. (2021). Trust Evaluation Mechanism of Service Nodes Based on Blockchain. In: Tan, Y., Shi, Y., Zomaya, A., Yan, H., Cai, J. (eds) Data Mining and Big Data. DMBD 2021. Communications in Computer and Information Science, vol 1453. Springer, Singapore. https://doi.org/10.1007/978-981-16-7476-1_21
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DOI: https://doi.org/10.1007/978-981-16-7476-1_21
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