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k-Trustee: Location Injection Attack-resilient Anonymization for Location Privacy

Lei, Jin and Chao, Li and Balaji, Palanisamy and James, Joshi (2018) k-Trustee: Location Injection Attack-resilient Anonymization for Location Privacy. Computers & Security, 78. pp. 212-230. ISSN 0167-4048

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Abstract

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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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Lei, Jinlej17@pitt.edulej17
Chao, Lichl205@pitt.educhl205
Balaji, Palanisamybpalan@pitt.edu
James, Joshijjoshi@pitt.edu
Date: September 2018
Date Type: Publication
Journal or Publication Title: Computers & Security
Volume: 78
Publisher: Elsevier
Page Range: pp. 212-230
DOI or Unique Handle: 10.1016/j.cose.2018.07.002
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISSN: 0167-4048
Official URL: https://www.sciencedirect.com/science/article/pii/...
Article Type: Research Article
Date Deposited: 19 Dec 2018 13:40
Last Modified: 19 Dec 2018 13:40
URI: http://d-scholarship.pitt.edu/id/eprint/35113

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