CRMANIJul 15, 2020

Cloud-based Privacy-Preserving Collaborative Consumption for Sharing Economy

arXiv:2007.07499v114 citations
AI Analysis

This addresses privacy concerns for users in collaborative consumption applications, though it is incremental as it builds on existing cryptographic methods.

The paper tackles the problem of data privacy in cloud-based sharing economy platforms by developing privacy-preserving protocols using homomorphic Paillier cryptosystems, enabling fair cost-sharing among users while preventing the cloud operator from tracking individual schedules or demands.

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.

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