What is it about?

we conduct a comprehensive survey on differentiated location privacy protection (DLPP) from semantic perception perspective to provide a complete overview of mobile semantics aware-DLPP (MS-DLPP). Specifically, we first summarize mobile-semantic representation methods systematically to sort out the semantic association between user and location in mobile scenarios. It also motivates to extend the development scope of MS-DLPP, considering that mobile semantics have not yet been exploited sufficiently in LPP. Subsequently, we review existing research works on DLPP by taking the dug mobile semantics as a clue. In these works, the authors perceive the differentiated privacy sensitivity of user mobility, or the user's personalized privacy-preserving requirements, by characterizing the above mobile semantics.

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Why is it important?

Combined with extensive open-source web information, user social-behavioral semantics raise different levels of privacy concerns to users. We name it the differentiated privacy sensitivity. It makes users have personalized requirements for protecting their travelings. This results in the inevitable evolutionary trend from location privacy protection (LPP) to differentiated location privacy protection (DLPP).

Perspectives

DLPP digs into mobile semantics between user and location in user social mobility by simulating the potential attacks to characterize the differentiated location sensitivity. It eanbles to provide location privacy protection with differentiated strength. Differentiated and appropriate strength well balances the tradeoff between privacy protection and application QoS.

Guoying Qiu
Southwest University

Read the Original

This page is a summary of: Differentiated Location Privacy Protection in Mobile Communication Services: A Survey from the Semantic Perception Perspective, ACM Computing Surveys, August 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3617589.
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