Spatiotemporal correlation-aware dummy-based privacy protection scheme for location-based services

Liu, Hai; Li, Xinghua; Li, Hui; Ma, Jianfeng; Ma, Xindi

doi:10.1109/infocom.2017.8056978

Cited by 84 publications

(58 citation statements)

References 24 publications

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“…In [19], the authors first proposed a technique of randomly generating dummies to complete anonymity, but the generated dummies have weak authenticity and can be easily identified. The methods in [20][21][22][23][24][25] study how to generate more realistic dummy trajectories. In [20], the authors presented trajectory k-anonymity, using the users' historical trajectory data to generate k − 1 dummy trajectories.…”

Section: Scenariomentioning

confidence: 99%

“…An effective approach is to maintain the quality of service while ensuring that users' privacy is not leaked. Considering that the dummy techniques [13,[17][18][19][20][21][22][23][24][25][26][27] to protect the privacy of a user are to add dummy queries to the real query and do not reduce the quality of the service. They are feasible in our work.…”

Section: Introductionmentioning

confidence: 99%

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DGS-HSA: A Dummy Generation Scheme Adopting Hierarchical Structure of the Address

Wang

Yang

et al. 2020

Applied Sciences

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With the increasing convenience of location-based services (LBSs), there have been growing concerns about the risk of privacy leakage. We show that existing techniques fail to defend against a statistical attack meant to infer the user’s location privacy and query privacy, which is due to continuous queries that the same user sends in the same location in a short time, causing the user’s real location to appear consecutively more than once and the query content to be the same or similar in the neighboring query. They also fail to consider the hierarchical structure of the address, so locations in an anonymous group may be located in the same organization, resulting in leaking of the user’s organization information and reducing the privacy protection effect. This paper presents a dummy generation scheme, considering the hierarchical structure of the address (DGS-HSA). In our scheme, we introduce a novel meshing method, which divides the historical location dataset according to the administrative region division. We also choose dummies from the historical location dataset with the two-level grid structure to realize the protection of the user’s location, organization information, and query privacy. Moreover, we prove the feasibility of the presented scheme by solving the multi-objective optimization problem and give the user’s privacy protection parameters recommendation settings, which balance the privacy protection level and system overhead. Finally, we evaluate the effectiveness and the correctness of the DGS-HSA through theoretical analysis and extensive simulations.

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Section: Scenariomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

DGS-HSA: A Dummy Generation Scheme Adopting Hierarchical Structure of the Address

Wang

Yang

et al. 2020

Applied Sciences

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“…In [22], the techniques can be classified as spatial anonymization, obfuscation, and private retrieval methods. Another classification is proposed in [23], where the different methods are categorized as dummy-based, K-anonymity, differential privacy, and cryptography. Unlike the previous classifications, we present the related work according to performance for a single user and a batch of users.…”

Section: Related Workmentioning

confidence: 99%

Batching Location Cloaking Techniques for Location Privacy and Safety Protection

Galdames

Gutiérrez-Soto

Curiel

2019

Mobile Information Systems

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Location-based services (LBSs) have become a profitable market because they offer real-time and local information to their users. Although several benefits are obtained from the usage of LBSs, they have opened up many privacy and safety challenges because a user needs to release his/her location. To tackle these challenges, many location-cloaking techniques have been proposed. Even though these solutions are effective in protecting either location privacy or location safety, they do not provide unified protection. Furthermore, most of them do not address the potential bottleneck in the anonymity server as a high demand of location and safety protection is requested. Finally, they do not take into account the potential impact of processing a large amount of location-cloaked queries. This paper deals with the efficient construction of location-cloaking areas for many users, who have both privacy and safety requirements. To achieve this goal, the construction of location-cloaking areas is carried out in batches. The LBSs’ batch processing takes advantage of users who are close to each other and who have similar requirements. Two batching techniques to build cloaking regions are analyzed using simulations. Empirical results show our techniques are able to balance the anonymizer workload, quality of location privacy and safety protection, and LBS workload.

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“…To protect users' location privacy during usage of location based services (LBS), various location privacy protection mechanisms have been proposed. Based on their core ideas, these mechanisms can be broadly categorized into approaches that use dummies [29,32], space transformation [18,28], mix-zone [6,36], encryption [31], spatial cloaking [5,10,17,20,21,27,30,34,40,43] and differential privacy [3,22,42]. The basic ideas behind these techniques are briefly discussed as follows.…”

Section: Related Workmentioning

confidence: 99%

k-Trustee: Location injection attack-resilient anonymization for location privacy

Jin

Palanisamy

Joshi

2018

Computers & Security

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Cloaking-based location privacy preserving mechanisms have been widely adopted to protect users' location privacy when using location-based services. A fundamental limitation of such mechanisms is that users and their location information in the system are inherently trusted by the Anonymization Server without any verification. In this paper, we show that such an issue could lead to a new class of attacks called location injection attacks which can successfully violate users' in-distinguishability (guaranteed by k-Anonymity) among a set of users. We propose and characterize location injection attacks by presenting a set of attack models and quantify the costs associated with them. We then propose and evaluate k-Trustee, a trust-aware location cloaking mechanism that is resilient to location injection attacks and guarantees a lower bound on the user's in-distinguishability. k-Trustee guarantees that each user in a given cloaked region can achieve the required privacy level of k-Anonymity by including at least k-1 other trusted users in the cloaked region. We demonstrate the effectiveness of k-Trustee through extensive experiments in a real-world geographic map and our experimental results show that the proposed cloaking algorithm guaranteeing k-Trustee is effective against various location injection attacks.

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Spatiotemporal correlation-aware dummy-based privacy protection scheme for location-based services

Cited by 84 publications

References 24 publications

DGS-HSA: A Dummy Generation Scheme Adopting Hierarchical Structure of the Address

DGS-HSA: A Dummy Generation Scheme Adopting Hierarchical Structure of the Address

Batching Location Cloaking Techniques for Location Privacy and Safety Protection

k-Trustee: Location injection attack-resilient anonymization for location privacy

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