Blockchain-based incentives for secure and collaborative data sharing in multiple clouds

M Shen, J Duan, L Zhu, J Zhang, X Du… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
IEEE Journal on Selected Areas in Communications, 2020ieeexplore.ieee.org
The prosperity of cloud computing has driven an increasing number of enterprises and
organizations to store their data on private or public cloud platforms. Due to the limitation of
individual data owners in terms of data volume and diversity, data sharing over different
cloud platforms would enable third parties to take advantage of big data analysis techniques
to provide value-added services, such as providing healthcare services for customers by
gathering medical data from multiple hospitals. However, it remains a challenging task to …
The prosperity of cloud computing has driven an increasing number of enterprises and organizations to store their data on private or public cloud platforms. Due to the limitation of individual data owners in terms of data volume and diversity, data sharing over different cloud platforms would enable third parties to take advantage of big data analysis techniques to provide value-added services, such as providing healthcare services for customers by gathering medical data from multiple hospitals. However, it remains a challenging task to design effective incentives that encourage secure and collaborative data sharing in multiple clouds. In this paper, we propose a reliable collaboration model consisting of three types of participants, which include data owners, miners, and third parties, where the data is shared via blockchain and recorded by a smart contract. In general, these participants may acquire and store the sharing of data using their private or public clouds. We analyze the topological relationships between the participants and develop some Shapley value models from simple to complicate in the process of revenue distribution. We also discuss the incentive effect of sharing security data and rationality of the designed solution through analysis towards distribution rules.
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