An anonymous entropy-based location privacy protection scheme in mobile social networks

Lina Ni,Fulong Tian,Qinghang Ni,Yan Yan,Jinquan Zhang

doi:10.1186/s13638-019-1406-4

Abstract

The popularization of mobile communication devices and location technology has spurred the increasing demand for location-based services (LBSs). While enjoying the convenience provided by LBS, users may be confronted with the risk of privacy leakage. It is very crucial to devise a secure scheme to protect the location privacy of users. In this paper, we propose an anonymous entropy-based location privacy protection scheme in mobile social networks (MSN), which includes two algorithms K-DDCA in a densely populated region and K-SDCA in a sparsely populated region to tackle the problem of location privacy leakage. The K-DDCA algorithm employs anonymous entropy method to select user groups and construct anonymous regions which can guarantee the area of the anonymous region formed be moderate and the diversity of the request content. The K-SDCA algorithm generates a set of similar dummy locations which can resist the attack of adversaries with background information. Particularly, we present the anonymous entropy method based on the location distance and request contents. The effectiveness of our scheme is validated through extensive simulations, which show that our scheme can achieve enhanced privacy preservation and better efficiency.

Highlights

Nowadays, the Internet of Things (IoT) is building a connected world seamlessly and enhancing the quality of our daily life throughout applications coming from consumer, commercial, industrial, and infrastructure spaces [1,2,3]
3) We propose the anonymous entropy method to effectively and securely select user groups based on the location distance and request contents and further construct anonymous regions, which can guarantee that the area of the anonymous region formed be moderate, and ensure the diversity of the request content
We propose the anonymous entropy method comprehensively considering the distance between the request users and the difference of the request contents, which can effectively protect the privacy of the users. 4.3 kd-tree algorithm kd-tree is a kind of balanced binary tree that divides data points in k-dimensional space, which is mainly applied to the search of key data in multi-dimensional space [24, 25]

Summary

Introduction

The Internet of Things (IoT) is building a connected world seamlessly and enhancing the quality of our daily life throughout applications coming from consumer, commercial, industrial, and infrastructure spaces [1,2,3]. It provides more intelligent services and makes them more efficient via accessing to and storage as well as processing of data [4,5,6,7]. The location privacy protection is of crucial challenge [15, 16]

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Results

Conclusion