Abstract
Deduplication has been extensively studied in terms of cloud data security and privacy. However, whether a deduplication scheme can be practically adopted is rarely investigated. Researchers have discussed the impact of economic facts and incentive mechanisms in motivating the acceptance of deduplication, but they either did not deeply explore this issue or failed to propose an effective solution. This chapter employs game theory to capture the interactions between stakeholders in two types of deduplication schemes: a server-controlled deduplication scheme (S-DEDU) and a client-controlled deduplication scheme. We propose a bounded discount-based incentive mechanism in S-DEDU, which attracts data users to participate. We also design an individualized discount-based incentive mechanism for motivating data holders to behave cooperatively and protecting data privacy at the same time. Furthermore, we conduct realistic dataset-based experiments to demonstrate the validity of our incentive mechanisms for motivating the adoption of deduplication. In the end, we summarize this chapter and propose prospective research outlooks.
| Original language | English |
|---|---|
| Title of host publication | Data Deduplication Approaches |
| Subtitle of host publication | Concepts, Strategies, and Challenges |
| Publisher | Elsevier |
| Pages | 335-356 |
| Number of pages | 22 |
| ISBN (Electronic) | 9780128233955 |
| DOIs | |
| State | Published - 1 Jan 2020 |
Keywords
- Deduplication
- Free-riding
- Game theory
- Incentive mechanism
- Nash equilibrium
- Utility
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