MobiHide: A Mobilea Peer-to-Peer System for Anonymous Location-Based Queries

Ghinita, Gabriel; Kalnis, Panos; Skiadopoulos, Spiros

doi:10.1007/978-3-540-73540-3_13

Cited by 142 publications

(134 citation statements)

References 9 publications

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“…To avoid the use of TTP, many mobile device-based schemes [4,6,9,10,14,15,[29][30][31][32][33] are introduced into LBS privacy protection LBS system. However, k-anonymity based schemes [10,13,[29][30][31][32][33] still need to generate CR via exchanged information from other encountered mobile users.…”

Section: Location Privacy Protectionmentioning

confidence: 99%

“…However, k-anonymity based schemes [10,13,[29][30][31][32][33] still need to generate CR via exchanged information from other encountered mobile users. Thus, they also cannot resist homogeneity attacks and background knowledge attacks.…”

Section: Location Privacy Protectionmentioning

confidence: 99%

“…Standard Hilbert curve (SHC) has been applied to some privacy protection schemes (e.g., [30,32]), which is different from our MHC. Our MHC mapping is similar to the VHCmapping [15], but there are several key differences.…”

Section: Location Privacy Protectionmentioning

confidence: 99%

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A Context‐Aware Location Differential Perturbation Scheme for Privacy‐Aware Users in Mobile Environment

Zhang

Huang

et al. 2018

Wireless Communications and Mobile Computing

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The proliferation of location-based services, representative services for the mobile networks, has posed a serious threat to users' privacy. In the literature, several privacy mechanisms have been proposed to preserve location privacy. Location obfuscation enforced using cloaking region is a widely used technique to achieve location privacy. However, it requires a trusted third-party (TTP) and cannot sufficiently resist various inference attacks based on background information and thus is vulnerable to location privacy breach. In this paper, we propose a context-aware location privacy-preserving solution with differential perturbations, which can enhance the user's location privacy without requiring a TTP. Our scheme utilizes the modified Hilbert curve to project every 2-d location of the user in the considered map to 1-d space and randomly generates the reasonable perturbation by adding Laplace noise via differential privacy. In order to solve the resource limitation of mobile devices, we use a quad-tree based scheme to transform and store the user context information as bit stream which achieves the high compression ratio and supports efficient retrieval. Security analysis shows that our proposed scheme can effectively preserve the location privacy. Experimental evaluation shows that our scheme retrieval accuracy is increased by an average of 15.4% compared with the scheme using standard Hilbert curve. Our scheme can provide strong privacy guarantees with a bounded accuracy loss while improving retrieval accuracy.

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Section: Location Privacy Protectionmentioning

confidence: 99%

Section: Location Privacy Protectionmentioning

confidence: 99%

See 1 more Smart Citation

A Context‐Aware Location Differential Perturbation Scheme for Privacy‐Aware Users in Mobile Environment

Zhang

Huang

et al. 2018

Wireless Communications and Mobile Computing

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show abstract

“…Various models of privacy protection systems have been proposed to support privacy-preserving and efficient data communication between mobile clients and servers, including client/server models [4], trusted third party models [5,13,19] and distributed models [7,8]. While the client/server model is simpler to implement, due to the lack of global knowledge in client side, the protection cost is in general higher with lower protection quality.…”

Section: Related Workmentioning

confidence: 99%

De-anonymizable Location Cloaking for Privacy-Controlled Mobile Systems

Palanisamy

2015

Network and System Security

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Abstract. The rapid technology upgrades of mobile devices and the popularity of wireless networks significantly drive the emergence and development of Location-based Services (LBSs), thus greatly expanding the business of online services and enriching the user experience. However, the personal location data shared with the service providers also leave hidden risks on location privacy. Location anonymization techniques transform the exact location of a user into a cloaking area by including the locations of multiple users in the exposed area such that the exposed location is indistinguishable from that of the other users. However in such schemes, location information once perturbed cannot be recovered from the cloaking region and as a result, users of the location cannot obtain fine granular information even when they have access to it. In this paper, we propose Dynamic Reversible Cloaking (DRC) a new de-anonymziable location cloaking mechanism that allows to restore the actual location from the perturbed information through the use of an anonymization key. Extensive experiments using realistic road network traces show that the proposed scheme is efficient, effective and scalable.

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“…The privacy is generally measured by K-anonymity [6,7] requirements. Two main approaches have been proposed for location anonymizing: centralized [8][9][10][11][12][13] and decentralized [14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Cloaking locations for anonymous location based services: a hybrid approach

Zhang

Huang

2008

Geoinformatica

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Abstract. An important privacy issue in Location Based Services(LBS) is to hide a user's identity while still provide quality location based services. Previous work has addressed the problem of locational K-anonymity either based on centralized or decentralized schemes. However, a centralized scheme relies on an anonymizing server(AS) for location cloaking, which may become the performance bottleneck when there are large number of clients. More importantly, holding information in a centralized place is more vulnerable to malicious attacks. A decentralized scheme depends on peer communication to cloak locations and is more scalable. However, it may pose too much computation and communication overhead to the clients. The service fulfillment rate may also be unsatisfied especially when there are not enough peers nearby. This paper proposes a new hybrid framework called HiSC that balances the load between the AS and mobile clients. HiSC partitions the space into base cells and a mobile client claims a surrounding area consisting of base cells. The number of mobile clients in the surrounding cells is kept and updated at both client and AS sides. A mobile client can either request cloaking service from the centralized AS or use a peer-to-peer approach for spatial cloaking based on personalized privacy, response time, and service quality requirements. HiSC can elegantly distribute the work load between the AS and the mobile clients by tuning one system parameter base cell size and two client parameters -surrounding cell size and tolerance count. By integrating salient features of two schemes, HiSC successfully preserves query anonymity and provides more scalable and consistent service. Both the AS and the clients can enjoy much less work load. Additionally, we propose a simple yet effective RRS(random range shifting)algorithm to prevent possible privacy leakage that would exist in the original P2P approach. Our experiments show that HiSC can elegantly balance the work load based on privacy requirements and client distribution. HiSC provides close to optimal service quality. Meanwhile, it reduces the response time by more than an order of magnitude from both the P2P scheme and the centralized scheme when anonymity level(value of K) or number of clients is large. It also reduces the update message cost of the AS by nearly 6 times and the peer searching message cost of the clients by more than an order of magnitude.

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MobiHide: A Mobilea Peer-to-Peer System for Anonymous Location-Based Queries

Cited by 142 publications

References 9 publications

A Context‐Aware Location Differential Perturbation Scheme for Privacy‐Aware Users in Mobile Environment

A Context‐Aware Location Differential Perturbation Scheme for Privacy‐Aware Users in Mobile Environment

De-anonymizable Location Cloaking for Privacy-Controlled Mobile Systems

Cloaking locations for anonymous location based services: a hybrid approach

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