Name
Abstract | ||
|---|---|---|
Cloud computing has been a dominant paradigm for a variety of information processing platforms, particularly for enabling various popular applications of sharing economy. However, there is a major concern regarding data privacy on these cloud-based platforms. This work presents novel cloud-based privacy-preserving solutions to support collaborative consumption applications for sharing economy. In typical collaborative consumption, information processing platforms need to enable fair cost-sharing among multiple users for utilizing certain shared facilities and communal services. Our cloud-based privacy-preserving protocols, based on homomorphic Paillier cryptosystems, can ensure that the cloud-based operator can only obtain an aggregate schedule of all users in facility sharing, or a service schedule conforming to service provision rule in communal service sharing, but is unable to track the personal schedules or demands of individual users. More importantly, the participating users are still able to settle cost-sharing among themselves in a fair manner for the incurred costs, without knowing each other’s private schedules or demands. Our privacy-preserving protocols involve no other third party who may compromise privacy. We also provide an extensive evaluation study and a proof-of-concept system prototype of our protocols. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TCC.2020.3010235 | IEEE Transactions on Cloud Computing |
Keywords | DocType | Volume |
Cloud-based privacy-preserving,collaborative consumption,sharing economy,homomorphic cryptosystems | Journal | 10 |
Issue | ISSN | Citations |
3 | 2168-7161 | 0 |
PageRank | References | Authors |
0.34 | 17 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lingjuan Lyu | 1 | 33 | 4.61 |
| Sid Chi-Kin Chau | 2 | 0 | 0.34 |
| Nan Wang | 3 | 0 | 0.34 |
| Yifeng Zheng | 4 | 253 | 23.96 |