Investigating the Adoption of Hybrid Encrypted Cloud Data Deduplication with Game Theory

Xueqin Liang, Zheng Yan*, Robert Deng, Qinghua Zheng

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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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.

Original languageEnglish
Pages (from-to)587-600
Number of pages14
JournalIEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
Volume32
Issue number3
DOIs
Publication statusPublished - Mar 2021
MoE publication typeA1 Journal article-refereed

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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