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Distributed Trusted Computing for Blockchain-Based Crowdsourcing

Yihuai Liang, Yan Li, Byeong-Seok Shin*

Department of Electrical and Computer Engineering, Inha University, Incheon, 22212, Korea

* Corresponding Author: Byeong-Seok Shin. Email:

(This article belongs to this Special Issue: Advances of AI and Blockchain technologies for Future Smart City)

Computers, Materials & Continua 2021, 68(3), 2825-2842.


A centralized trusted execution environment (TEE) has been extensively studied to provide secure and trusted computing. However, a TEE might become a throughput bottleneck if it is used to evaluate data quality when collecting large-scale data in a crowdsourcing system. It may also have security problems compromised by attackers. Here, we propose a scheme, named dTEE, for building a platform for providing distributed trusted computing by leveraging TEEs. The platform is used as an infrastructure of trusted computations for blockchain-based crowdsourcing systems, especially to securely evaluate data quality and manage remuneration: these operations are handled by a TEE group. First, dTEE uses a public blockchain with smart contracts to manage TEEs without reliance on any trusted third parties. Second, to update TEE registration information and rule out zombie TEEs, dTEE uses a reporting mechanism. To attract TEE owners to join in and provide service of trusted computations, it uses a fair monetary incentive mechanism. Third, to account for malicious attackers, we design a model with Byzantine fault tolerance, not limited to a crash-failure model. Finally, we conduct an extensive evaluation of our design on a local cluster. The results show that dTEE finishes evaluating 10,000 images within one minute and achieves about 65 tps throughput when evaluating Sudoku solution data with collective signatures both in a group of 120 TEEs.


Cite This Article

Y. Liang, Y. Li and B. Shin, "Distributed trusted computing for blockchain-based crowdsourcing," Computers, Materials & Continua, vol. 68, no.3, pp. 2825–2842, 2021.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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