Research on Hybrid-Cloud-Based User Privacy Protection of O2O Platform

Abstract

O2O (Online-to-Offline) is a new rapidly growing e-commerce model. It combines offline physical business with online network marketing and electronic payment to provide convenient and efficient localized services for consumers. However, user privacy concerns have become one of the challenging issues affecting further O2O e-commerce applications. Taking the catering takeaway O2O e-commerce as an example, the user privacy and cost issues occurring in the big data era are presented through analyzing of the service model of current mainstream catering takeaway platforms. A hybrid-cloud-based privacy preserving application framework for catering takeaway O2O e-commerce is proposed. The similarities between users are calculated using SimRank model and user-restaurant relationship diagram. Considering their personalized privacy requirements, the users are grouped and anonymized. Even if the attacker obtains all the transaction information stored on the public cloud, the transaction relationship of a specific order cannot be uniquely identified. The feasibility and effectiveness of the proposed user privacy protection method is illustrated by an example.