Investigating the Adoption of Hybrid Encrypted Cloud Data Deduplication with Game Theory
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Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2021-03
Department
Major/Subject
Mcode
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Language
en
Pages
14
587-600
587-600
Series
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, Volume 32, issue 3
Abstract
Encrypted data deduplication, along with different preferences in data access control, brings the birth of hybrid encrypted cloud data deduplication (H-DEDU for short). However, whether H-DEDU can be successfully deployed in practice has not been seriously investigated. Obviously, the adoption of H-DEDU depends on whether it can bring economic benefits to all stakeholders. But existing economic models of cloud storage fail to support H-DEDU due to complicated interactions among stakeholders. In this paper, we establish a formal economic model of H-DEDU by formulating the utilities of all involved stakeholders, i.e., data holders, data owners, and Cloud Storage Providers (CSPs). Then, we construct a multi-stage Stackelberg game, which consists of Holder Participation Game, Owner Online Game and CSP Pricing Game, to capture the interactions among all system stakeholders. We further analyze the conditions of the existence of a sub-game perfect Nash Equilibrium and propose a gradient-based algorithm to help the stakeholders choose near-optimal strategies. Extensive experiments show the feasibility of the proposed algorithm in achieving the Nash Equilibrium of the Stackelberg game. Additionally, we investigate the effects of parameters related to CSP, data owners and data holders on H-DEDU adoption. Our study advises all stakeholders the best strategies to adopt H-DEDU.Description
Keywords
Biological system modeling, Cloud computing, Cloud Computing, Cryptography, Deduplication, Economics, Game theory, Games, Gradient-Based Algorithm, Multi-Stage Stackelberg Game, Stakeholders
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Citation
Liang, X, Yan, Z, Deng, R & Zheng, Q 2021, ' Investigating the Adoption of Hybrid Encrypted Cloud Data Deduplication with Game Theory ', IEEE Transactions on Parallel and Distributed Systems, vol. 32, no. 3, pp. 587-600 . https://doi.org/10.1109/TPDS.2020.3028685
