Method of trajectory privacy protection based on restraining trajectory in LBS

Zhao, Zhijin; Wang, Jiabo; Sun, Chuanlin; Yuan, Youwei; Li, Bin

doi:10.1504/ijict.2018.094321

Cited by 2 publications

(2 citation statements)

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“…Although numerous location protection methods have been presented over the last ten years, they either lack necessary privacy protection or have too high computational costs with precise mathematical justification. There are several types of methods used to protect location privacy at home and abroad: the first one is suppression method, 3 which is to protect user privacy by suppressing sensitive background information based on a priori knowledge. However, in order to achieve better protection performance, this method needs to delete too much data, which leads to a large amount of data loss and low data availability.…”

Section: Introductionmentioning

confidence: 99%

DLPM: A dynamic location protection mechanism supporting continuous queries

Zhu

Hong

Xie

et al. 2022

Concurrency and Computation

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Summary Currently, the protection of users' location privacy, particularly for moveable users, is a major concern for both academia and business. In order to receive required services, a moveable user needs to constantly disclose his/her location information with an untrusted third party in his/her locations, which raises security and privacy issues. To settle the above problems, in this work, we creatively integrate local differential privacy (LDP) with conditional random field (CRF) to facilitate continuous location sharing among moveable users. Firstly, we advance a novel approach of employing CRF to represent users' mobility. After that, we establish a system to provide continuous location sharing by combining the δ$$ \delta $$‐location set and ε$$ \varepsilon $$‐LDP. Finally, we evaluate the system performance on actual data sets. The experimental results indicate that our technique outperforms the planar isotropic mechanism (PIM) and AGENT.

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Section: Introductionmentioning

confidence: 99%

DLPM: A dynamic location protection mechanism supporting continuous queries

Zhu

Hong

Xie

et al. 2022

Concurrency and Computation

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“…Chen and Deng (2018) proposed a scheme to protect privacy information including location, identity, and domain, while the user can still obtain the required service from a service provider. The privacy protection method based on LBS constraint trajectory proposed by Zhao et al (2018) is to select the non-sensitive location with the maximum probability that the user may stay to replace the sensitive location by inhibiting the release of the sensitive location, so as to prevent the leakage of the sensitive location of the user's trajectory. Besides, both the privacy protection in wireless sensor networks (Khenous et al, 2018;Ozdemir et al, 2014) and the privacy issues in V2G networks (Han and Xiao, 2016) are to improve the service quality of data on the basis of privacy protection.…”

Section: Introductionmentioning

confidence: 99%

Location big data differential privacy dynamic partition release method

Yan

Zhang

Wang

et al. 2020

IJSN

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Aiming at the privacy protection requirements in real-time statistical publishing process of location big data, a dynamic partition method is proposed based on differential privacy mechanism. The temporal redundancy between adjacent data snapshots has been eliminated by sampling and differential processing of dynamic location big data, and the spatial redundancy of location big data has been reduced by adaptive density meshing and uniformity heuristic quadtree partitioning. Differential privacy protection has been realised by adjusting partition structures of the current dataset on the spatial structure of previous moment and adding Laplace noise. Experiments carried out on the cloud computing platform and real location big datasets show that the proposed algorithm can meet the dynamic partition release requirements of real-time location big data, and the query precision of single-released location big data is better than other similar methods.

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Method of trajectory privacy protection based on restraining trajectory in LBS

Cited by 2 publications

References 0 publications

DLPM: A dynamic location protection mechanism supporting continuous queries

DLPM: A dynamic location protection mechanism supporting continuous queries

Location big data differential privacy dynamic partition release method

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