中国邮电高校学报(英文) ›› 2015, Vol. 22 ›› Issue (2): 44-51.doi: 10.1016/S1005-8885(15)60638-0

• Artificial Intelligence • 上一篇    下一篇

Triggered query with strong location privacy in mobile network

杨松涛1,马春光2,周长利3   

  1. 1. 佳木斯大学
    2. 哈尔滨工程大学保密学院
    3. 哈尔滨工程大学
  • 收稿日期:2014-03-07 修回日期:2014-10-03 出版日期:2015-04-30 发布日期:2015-04-22
  • 通讯作者: 马春光 E-mail:machunguang@hrbeu.edu.cn

Triggered query with strong location privacy in mobile network

Song-Tao YANG1,   

  • Received:2014-03-07 Revised:2014-10-03 Online:2015-04-30 Published:2015-04-22

摘要: Location privacy is a hot-button topic that has to be taken into account if location-based services (LBS) are to succeed. Extensive researches focus on the nearest neighbor (NN) query or k-nearest neighbor (kNN) query about location privacy-preserving. However, no single technique can be applied to any situation and achieve high security and low cost. This manuscript focuses on the location privacy-preserving in the geo-fencing services, A secure two-party computation location privacy model and the corresponding solution was proposes based on triggered query. The author draw on the computational geometry and cryptography technologies, mainly to conquer such problems related to the users’ location hidden, secret checking-in and secret authentication in the geo-fencing services. Performance assessment shows that the proposed solution can reduce the query-processing time and the size of query result set.

关键词: privacy-preserving, location-based service, secure two-party computation, triggered query, geo-fencing services

Abstract: Location privacy is a hot-button topic that has to be taken into account if location-based services (LBS) are to succeed. Extensive researches focus on the nearest neighbor (NN) query or k-nearest neighbor (kNN) query about location privacy-preserving. However, no single technique can be applied to any situation and achieve high security and low cost. This manuscript focuses on the location privacy-preserving in the geo-fencing services, A secure two-party computation location privacy model and the corresponding solution was proposes based on triggered query. The author draw on the computational geometry and cryptography technologies, mainly to conquer such problems related to the users’ location hidden, secret checking-in and secret authentication in the geo-fencing services. Performance assessment shows that the proposed solution can reduce the query-processing time and the size of query result set.

Key words: privacy-preserving, location-based service, secure two-party computation, triggered query, geo-fencing services