A location privacy protection strategy based on differential privacy

Abstract

The invention provides a system solution for protecting position privacy on the premise of strictly ensuring privacy, belonging to the field of data information security. For most spatial transformation techniques, the proposed method relies on semantic privacy model, such as k-anonymous, or ad hoc uncertainty models that do not provide strict privacy. Many of them consider only static scenarios or disturbance locations on a single timestamp, rather than the temporal dependency of the mobile user's location, and are therefore vulnerable to various inferential attacks to propose solutions. Firstly, according to the topological relation of the geographic space, the algorithm is proposed to calculate the privacy level of each region on the map. Secondly, a differential privacy based onsigma-location set is proposed to protect the real position of each time point, and the sensitivity package is used to capture the geometric meaning of two-dimensional sensitivity. Finally, a special position perturbation mechanism is proposed to implement the algorithm based on sigma-Differential privacy of the location set.

Description

technical field [0001] The invention belongs to the field of data information security, and relates to a location privacy protection strategy based on differential privacy. Background technique [0002] With the use of smartphones there is a huge opportunity for location-based applications. Location-Based Services (LBS) From searching for points of interest to location-based gaming and location-based commerce. Location-based social networking allows users to share locations with friends, friends, and provide suggestions about points of interest based on their location. A major concern of location-based applications is location privacy. To use these applications, users must provide their location to the respective service providers or other third parties. This location disclosure raises important privacy concerns, as user location may expose them to attacks ranging from unwanted location-based spam / scams to blackmail and even physical danger. [0003] Most existing soluti...

AI Technical Summary

Problems solved by technology

Finally, there is no effective location publishing mechanism under this model

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