LRM: A Location Recombination Mechanism for Achieving Trajectory $k$ -Anonymity Privacy Protection

Chen, Yuling; Luo, Shoushan; Xin, Yang; Zhu, Hongliang; Chen, Yuling; Yang, Guangcan; Yang, Yixian

doi:10.1109/access.2019.2960008

Cited by 13 publications

(12 citation statements)

References 38 publications

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“…These schemes are DLS [ 13 ], EDLS [ 13 ], MOS [ 19 ], K-DLCA [ 20 ], etc. For trajectory privacy protection, Wang et al [ 21 ] construct a probabilistic model based on historical location data. The model calculates the location access probability and location transfer probability.…”

Section: Related Workmentioning

confidence: 99%

GL-Tree: A Hierarchical Tree Structure for Efficient Retrieval of Massive Geographic Locations

Liu

Zhang

Xin

2023

Sensors

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Location-based application services and location privacy protection solutions are often required for the storage, management, and efficient retrieval of large amounts of geolocation data for specific locations or location intervals. We design a hierarchical tree-like organization structure, GL-Tree, which enables the storage, management, and retrieval of massive location data and satisfies the user’s location-hiding requirements. We first use Geohash encoding to convert the two-dimensional geospatial coordinates of locations into one-dimensional strings and construct the GL-Tree based on the Geohash encoding principle. We gradually reduce the location intervals by extending the length of the Geohash code to achieve geospatial grid division and spatial approximation of user locations. The hierarchical tree structure of GL-Tree reflects the correspondence between Geohash codes and geographic intervals. Users and their location relationships are recorded in the leaf nodes at each level of the hierarchical GL-Tree. In top–down order, along the GL-Tree, efficient storage and retrieval of location sets for specified locations and specified intervals can be achieved. We conducted experimental tests on the Gowalla public dataset and compared the performance of the B+ tree, R tree, and GL-Tree in terms of time consumption in three aspects: tree construction, location insertion, and location retrieval, and the results show that GL-Tree has good performance in terms of time consumption.

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Section: Related Workmentioning

confidence: 99%

GL-Tree: A Hierarchical Tree Structure for Efficient Retrieval of Massive Geographic Locations

Liu

Zhang

Xin

2023

Sensors

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“…[21] proposed a k-anonymity location privacy scheme based on an auction mechanism. To achieve trajectory k-anonymity privacy protection, [22] proposed Location Recombination Mechanism (LRM) which could generate k-1 fake trajectories similar to base trajectories in terms of geographical features and probabilistic features.…”

Section: Spatial Cloaking Location Privacy Protectionmentioning

confidence: 99%

TCA: A Trusted Collaborative Anonymity Construction Scheme for Location Privacy Protection in VANETs

2022

KSII TIIS

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As location-based services (LBS) are widely used in vehicular ad-hoc networks (VANETs), location privacy has become an utmost concern. Spatial cloaking is a popular location privacy protection approach, which uses a cloaking area containing k-1 collaborative vehicles (CVs) to replace the real location of the requested vehicle (RV). However, all CVs are assumed as honest in k-anonymity, and thus giving opportunities for dishonest CVs to submit false location information during the cloaking area construction. Attackers could exploit dishonest CVs' false location information to speculate the real location of RV. To suppress this threat, an edge-assisted Trusted Collaborative Anonymity construction scheme called TCA is proposed with trust mechanism. From the design idea of trusted observations within variable radius r, the trust value is not only utilized to select honest CVs to construct a cloaking area by restricting r's search range but also used to verify false location information from dishonest CVs. In order to obtain the variable radius r of searching CVs, a multiple linear regression model is established based on the privacy level and service quality of RV. By using the above approaches, the trust relationship among vehicles can be predicted, and the most suitable CVs can be selected according to RV's preference, so as to construct the trusted cloaking area. Moreover, to deal with the massive trust value calculation brought by large quantities of LBS requests, edge computing is employed during the trust evaluation. The performance analysis indicates that the malicious response of TCA is only 22% of the collaborative anonymity construction scheme without trust mechanism, and the location privacy leakage is about 32% of the traditional Enhanced Location Privacy Preserving (ELPP) scheme.

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“…The anonymity mechanism is mainly utilized to generate an anonymous set by means of generalization, bucketization, suppression, etc., so that the indistinguishable pairs in potential secrets reach the anonymity threshold. Researchers have proposed a variety of trajectory anonymity methods to ensure that the published trajectories meet specific threshold requirements [37]- [39]. Different algorithms improve the indistinguishability of protection targets by selecting different aggregation criteria.…”

Section: Related Work a Privacy-preserved Trajectory Data Publismentioning

confidence: 99%

Risk-Aware Individual Trajectory Data Publishing With Differential Privacy

et al. 2021

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LRM: A Location Recombination Mechanism for Achieving Trajectory $k$ -Anonymity Privacy Protection

Cited by 13 publications

References 38 publications

GL-Tree: A Hierarchical Tree Structure for Efficient Retrieval of Massive Geographic Locations

GL-Tree: A Hierarchical Tree Structure for Efficient Retrieval of Massive Geographic Locations

TCA: A Trusted Collaborative Anonymity Construction Scheme for Location Privacy Protection in VANETs

Risk-Aware Individual Trajectory Data Publishing With Differential Privacy

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