CRSIAug 1, 2012

Search Me If You Can: Privacy-preserving Location Query Service

arXiv:1208.0107v3137 citations
Originality Incremental advance
AI Analysis

This addresses privacy concerns for users of mobile and social network services, but appears incremental as it builds on existing privacy-preserving techniques.

The paper tackles the challenge of preserving location privacy while enabling utility in Location-Based Services by designing a novel fine-grained Privacy-preserving Location Query Protocol that allows different levels of encrypted location queries for users and is efficient for mobile platforms.

Location-Based Service (LBS) becomes increasingly popular with the dramatic growth of smartphones and social network services (SNS), and its context-rich functionalities attract considerable users. Many LBS providers use users' location information to offer them convenience and useful functions. However, the LBS could greatly breach personal privacy because location itself contains much information. Hence, preserving location privacy while achieving utility from it is still an challenging question now. This paper tackles this non-trivial challenge by designing a suite of novel fine-grained Privacy-preserving Location Query Protocol (PLQP). Our protocol allows different levels of location query on encrypted location information for different users, and it is efficient enough to be applied in mobile platforms.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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