Diverse Metrics for Robust LBS Privacy: Distance, Semantics, and Temporal Factors
Addressing inherent limitations in distinguishing metrics relying solely on Euclidean distance, especially within the context of geo-indistinguishability (Geo-I) as a protection mechanism for location-based service (LBS) privacy, this paper introduces an innovative and comprehensive metric. Our prop...
Main Authors: | Yongjun Li, Yuefei Zhu, Jinlong Fei, Wei Wu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-02-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/24/4/1314 |
Similar Items
-
Differential Privacy Preservation for Location Semantics
by: Liang Yan, et al.
Published: (2023-02-01) -
A Voronoi-Based Semantically Balanced Dummy Generation Framework for Location Privacy
by: Aditya Tadakaluru, et al.
Published: (2023-03-01) -
Effective and Privacy-Preserving Estimation of the Density Distribution of LBS Users under Geo-Indistinguishability
by: Jongwook Kim, et al.
Published: (2023-02-01) -
An Advanced Dummy Position-Based Privacy Provisioning Framework for TTP-Based LBS System
by: M. Usman Ashraf, et al.
Published: (2024-01-01) -
GLPS: A Geohash-Based Location Privacy Protection Scheme
by: Bin Liu, et al.
Published: (2023-11-01)