Cloud Edge-Client Collaborative Trajectory Privacy Protection System and Technology

Location-based service (LBS), with its personalized, real time, and mobile features, is one of the more popular mobile applications (apps) in the world today. However, under the centralized LBS architecture, the high dimensional trajectory data collected from LBS users are directly exposed to the central server, which entails serious privacy risks. Although existing privacy protection technologies can protect the private user trajectories to a certain extent, they often ignore the reasonable data requirements of LBS providers (e.g., data required to maintain or improve services). Focusing on the weaknesses of centralized LBS and the shortcomings of existing solutions, this article proposes a cloud edge-client collaborative trajectory privacy protection system. The system migrates LBS from the cloud to the network edge and balances privacy and utility--including service utility and data utility--with anonymous authentication, dummy location, and privacy risk evaluation mechanisms. The theoretical analysis and simulation results show that the system can effectively protect trajectory privacy under the premise of high availability of services and data, which is a significant improvement over the current LBS system.

Automated summary

This article proposes a cloud edge-client collaborative trajectory privacy protection system to address the privacy risks and shortcomings of existing solutions in centralized location-based services (LBS). By migrating LBS from the cloud to the network edge and implementing anonymous authentication, dummy location, and privacy risk evaluation mechanisms, the system effectively protects trajectory privacy while maintaining service and data availability, leading to significant improvements compared to current LBS systems.