Efficient secure similarity computation on encrypted trajectory data

An Liu, Kai Zhengy, Lu Li, Guanfeng Liu, Lei Zhao, Xiaofang Zhou

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

63 Citations (Scopus)

Abstract

Outsourcing database to clouds is a scalable and cost-effective way for large scale data storage, management, and query processing. Trajectory data contain rich spatio-temporal relationships and reveal many forms of individual sensitive information (e.g., home address, health condition), which necessitate them to be encrypted before being outsourced for privacy concerns. However, efficient query processing over encrypted trajectory data is a very challenging task. Though some achievements have been reported very recently for simple queries (e.g., SQL queries, kNN queries) on encrypted data, there is rather limited progress on secure evaluation of trajectory queries because they are more complex and need special treatment. In this paper, we focus on secure trajectory similarity computation that is the cornerstone of secure trajectory query processing. More specifically, we propose an efficient solution to securely compute the similarity between two encrypted trajectories, which reveals nothing about the trajectories, but the final result. We theoretically prove that our solution is secure against the semi-honest adversaries model as all the intermediate information in our protocols can be simulated in polynomial time. Finally we empirically study the efficiency of the proposed method, which demonstrates the feasibility of our solution.

Original languageEnglish
Title of host publication2015 IEEE 31st International Conference on Data Engineering, ICDE 2015
Place of PublicationNew York
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages66-77
Number of pages12
ISBN (Electronic)9781479979639
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event2015 31st IEEE International Conference on Data Engineering, ICDE 2015 - Seoul, Korea, Republic of
Duration: 13 Apr 201517 Apr 2015

Conference

Conference2015 31st IEEE International Conference on Data Engineering, ICDE 2015
CountryKorea, Republic of
CitySeoul
Period13/04/1517/04/15

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