A Client-Biased Cooperative Search Scheme in Blockchain-Based Data Markets
Lots of privacy and security issues in the current cloud-based data markets will be eliminated by taking advantage of blockchain-based decentralized storage services, which can provide a new paradigm for safe data outsourcing and correct remote search. However, existing data markets are also questio...
Saved in:
| Published in | Proceedings - International Conference on Computer Communications and Networks pp. 1 - 9 |
|---|---|
| Main Authors | , , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
01.07.2019
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 2637-9430 |
| DOI | 10.1109/ICCCN.2019.8847102 |
Cover
| Summary: | Lots of privacy and security issues in the current cloud-based data markets will be eliminated by taking advantage of blockchain-based decentralized storage services, which can provide a new paradigm for safe data outsourcing and correct remote search. However, existing data markets are also questioned on their inflexible and opaque pricing, where the value of data ownership and the cost of query search are mixed. Thus, a better pricing model is necessarily needed in an emerging decentralized data market. In this paper, we envision an Ethereum-based data market, in which the pricing model for each query includes two parties: owner (paid for his data ownership) and miner (rewarded by query search). We study a new cooperative search scheme through a proxy to reduce cost on the client (user) side. Suppose each user query is charged based on the number of keywords in the query. The cost reduction is based on combining multiple queries into a group subject to the constraint that the resulting combined query is not significantly larger than any of its original query in terms of the number of keywords. The total price is based on total number of keywords in all groups. As the optimal grouping depends on the pricing of both owner and miner, we build a small testbed to analyze how price setting will affect grouping results. Since it is a cooperative model with shared resources, we also study various incentive properties on the client side, thereby yielding a cost sharing mechanism to split joint cost in a truth-revealing and fair manner. |
|---|---|
| ISSN: | 2637-9430 |
| DOI: | 10.1109/ICCCN.2019.8847102 |