Differentiated Location Privacy Protection in Mobile Communication Services: A Survey from the Semantic Perception Perspective

Author:

Qiu Guoying1ORCID,Tang Guoming2ORCID,Li Chuandong1ORCID,Luo Lailong3ORCID,Guo Deke3ORCID,Shen Yulong4ORCID

Affiliation:

1. College of Electronic and Information Engineering, Southwest University, China

2. Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, China

3. Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology,China

4. School of Computer Science and Technology, Xidian University, China

Abstract

Mobile communication services raise user privacy concerns in sharing the traveling trajectories while facilitating people’s daily lives. According to these shared trajectories, adversaries can dig users’ multi-modal behavioral semantics by combining with extensive open-source web information. These behavioral semantics have differentiated privacy sensitivity, raising different levels of privacy concerns. It makes users have personalized requirements for protecting their travelings. Resulting in the inevitable evolutionary trend from location privacy protection to differentiated location privacy protection (DLPP). DLPP digs into mobile semantics and characterizes the differentiated location sensitivity by simulating the potential attacks. It provides the privacy protection with differentiated strength to each location. Differentiated and appropriate strength well balances the tradeoff between privacy protection and data availability for the quality of application service. We are motivated to conduct a comprehensive survey on DLPP from the semantic perception perspective. It forms a complete overview of the mobile semantics-aware differentiation in location privacy protection. Specifically, we first review the research works on multi-modal mobile semantic representation. Then, taking the dug semantics as a clue, we summarize the basic principles of DLPP research systematically. To complete the overview, we also summarize their design modes and discuss the open opportunities and challenges for future works.

Funder

Natural Science Foundation of China

Innovation Capability Support Program of Shaanxi

Jinan “20 New Colleges and Universities” Introduction and Innovation Team

Postdoctoral Science Foundation Special Funded Project of Chongqing

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Reference157 articles.

1. ADGAN: Protect Your Location Privacy in Camera Data of Auto-Driving Vehicles

2. A Location Privacy-Preserving System Based on Query Range Cover-Up or Location-Based Services

3. Please Forget Where I Was Last Summer: The Privacy Risks of Public Location (Meta)Data

4. Practical Location Privacy Attacks and Defense on Point-of-interest Aggregates

5. Lorenzo Gabrielli, Salvatore Rinzivillo, Francesco Ronzano, and Daniel Villatoro. 2013. From tweets to semantic trajectories: Mining anomalous urban mobility patterns. In Proceedings of the International Workshop on Citizen in Sensor Networks. 26–35.

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