Location privacy: going beyond K-anonymity, cloaking and anonymizers

Khoshgozaran, Ali; Shahabi, Cyrus; Shirani-Mehr, Houtan

doi:10.1007/s10115-010-0286-z

Cited by 90 publications

(66 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although, among them, policy-based approaches and cryptographybased approaches [14] have also been investigated, most existing works are based on location obfuscation. For location obfuscation mechanisms, most of them employ well-known location k-anonymity to protect user's privacy by blurring user's exact location into a sufficiently larger CR.…”

Section: Location Privacy Protectionmentioning

confidence: 99%

“…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%

“…To address the privacy issues for mobile users in LBSs, a variety of privacy-preserving mechanisms and metrics have been proposed to allow users to make use of the LBSs while mitigating privacy concerns over the past few years [3][4][5][6][7][8][9][10][11][12][13][14][15]. These LBS privacy protection mechanisms (LPPMs) provide different privacy-utility trade-off, which offer alternatives to better meet personal requirements of different mobile users.…”

Section: Introductionmentioning

confidence: 99%

“…These LBS privacy protection mechanisms (LPPMs) provide different privacy-utility trade-off, which offer alternatives to better meet personal requirements of different mobile users. Roughly speaking, these LPPMs can be divided into two categories according to their architecture [16]: trusted anonymization server-based schemes [3,5,7,8,11,13] and mobile devices-based schemes [4,6,9,10,14,15]. In trusted anonymization serve-based schemes, a trusted thirdparty server (e.g., anonymizer [3]) is employed to perturb, obfuscate, and cloak user's query location by using the notion of k-anonymity [3].…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, it incurs the high computation overhead at client-side. Mobile device-based approaches remove the requirement of a TTP by using k-anonymity [10,15], location obfuscation and perturbation [4,6,9], and private information retrieval (PIR) [14]. However, PIR may incur high computation and communication costs unaffordable to mobile devices and LBS server.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

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

Zhang

Huang

et al. 2018

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

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.

show abstract

Section: Location Privacy Protectionmentioning

confidence: 99%