摘要
提出了一种高效的保护隐私的轨迹相似度计算框架.基于安全的同态加密系统和Yao协议,该框架能够确保持有轨迹的两方不能得到除了轨迹相似度以外的其他任何信息,从而同时保护了两方的轨迹数据隐私.该框架针对轨迹相似度计算过程中的不同步骤具有不同的计算特点,交替使用同态加密系统和Yao协议,从而有效地提高了性能.实验结果表明本框架与已有的方法相比显著减少了计算开销.
In this paper, we propose a privacy preserving framework for efficient computation of trajectory similarity. Based on the well-known homomorphic encryption and Yao＇s protocol （a. k. a Yao＇s garbled circuits） which have been proved to be secure, this framework enables two parties to compute the similarity of their trajectories without revealing the actual trajectory to the other party. By exploring the computation characteristics in the course of trajectory similarity evaluation, this framework combines both homomorphic encryption and Yao＇s protocol, where each is used in a different step in the computation of trajectory similarity to improve the performance. Experimental results show that this framework can significantly reduce the computation time compared with existing methods.
出处
《华东师范大学学报（自然科学版）》
CAS
CSCD
北大核心
2015年第5期154-161,171,共9页
Journal of East China Normal University(Natural Science)
基金
国家自然科学基金(61303019
61402313)
国家自然科学基金重点项目(61232006)
关键词
轨迹相似度
隐私保护
同态加密
Yao协议
trajectory similarity, privacy preserving
homomorphic encryption
Yao＇s protocol
