About

Maintained by
Hui Zhu, Rongxing Lu, Cheng Huang, Le Chen and Hui Li
Xidian University
No.2 South Taibai Road, Xi’an, Shaanxi 710071, China

  Abstract

With the pervasiveness of location-aware mobile electronic devices and the advances of wireless communications, location-based services (LBS), which can help people enjoy a convenient life, has attracted considerable interest recently. However, the privacy issues of LBS are still challenging today. Aiming at the challenges, in this paper, we present a new efficient and privacy-preserving LBS query scheme in outsourced cloud, i.e., EPQ, for pervasive smartphones. In the EPQ scheme, the LBS provider's data are first outsourced to the cloud server in an encrypted manner, and then, a registered user can get accurate LBS query results without divulging his/her location information to the LBS provider and the cloud server. Specifically, based on an improved homomorphic encryption technique over a composite order group, a special spatial range query algorithm SRQC over ciphertext is proposed, with which EPQ achieves privacy preservation of user's query and confidentiality of LBS data in the outsourced cloud server. Through detailed security analysis, we show that EPQ can resist various known security threats. In addition, we also implement EPQ over a smartphone and three workstations with a real LBS data set, and extensive simulation results further demonstrate that the proposed EPQ scheme is highly efficient at the smartphone side and can be implemented effectively in the cloud server.

  System Model

  Prototype and user interface

(a) Prototype for LBS query.

(b) User interface of EPQ.apk.

  Computation complexity of EPQ

(a) Computation cost of the cloud server with different search ranges and region division.

(b) Computation cost of the LBS provider in data creation.

(c) Computation cost of the smartphone in LBS query generation.

(d) Computation cost of the smartphone in query result reading.

(e) Query response time in real environment.

(f) Average running time in cloud versus FINE.

  Demo Download

Demo Download:  
Demo File SHA256: 9AE1871D04B6D5AA79199AD00E6E77C6C02AE8838A244FF41D635FA8DDD5D353
For Source Code:    zhuhui@xidian.edu.cn