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Book ChapterDOI

Privacy in Location Based Services: Protection Strategies, Attack Models and Open Challenges

TLDR
A state-of-art survey of privacy in location based services containing details of all privacy protection schemes is presented, and attack models and their handling mechanism are discussed in comprehensive manner.
Abstract
The increasing capabilities of position determination technologies (e.g., GPS) in mobile and hand held device facilitates the widespread use of Location Based Services (LBS). Although LBSs are providing enhanced functionalities and convenience of ubiquitous computing, they open up new vulnerabilities that can be exploited to target violation of security and privacy of users. For these applications to perform, location of the individual/user is required. Consequently they may pose a major privacy threat on its users. So for LBS applications to succeed, privacy and confidentiality are key issues. “Privacy protection” has become the buzz word now days for the users of location based services. This problem has gained a considerable attention among the researcher community also. A state-of-art survey of privacy in location based services containing details of all privacy protection schemes is presented. Further, attack models and their handling mechanism are discussed in comprehensive manner. Finally, some open challenges in the area of location privacy are also demonstrated.

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Citations
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Journal ArticleDOI

Comprehensive Review: Privacy Protection of User in Location-Aware Services of Mobile Cloud Computing

TL;DR: This comprehensive research review will provide the challenge of protecting the privacy of user’s location in MCC; analyze several related works regarding the issue; and suggests possible solutions related to the issue, in light of few shortcomings which still needs attention.
Journal ArticleDOI

Improved Generalization for Secure Data Publishing

TL;DR: Three new generalization techniques are proposed including conventional generalization hierarchies, divisors based generalized hierarchies and cardinality-based generalization hierarchical techniques, which outperforms among the existing techniques in terms of better utility.
Journal ArticleDOI

Internet of Spatial Things: A New Reference Model With Insight Analysis

TL;DR: This paper draws an inspiration towards the perspective vision of the IoST, which is concerned with revise IoT with the spatial perspective, and the Io ST concept is argued by the presentation of its definition and architectural components.
Journal ArticleDOI

Incentivizing Crowdsensing-Based Noise Monitoring with Differentially-Private Locations

TL;DR: A group-differentially-private game-theoretical solution that enables the indistinguishability of workers’ locations and sensing data without the help of a trusted entity while meeting the accuracy demands of crowd sensing tasks.
Journal ArticleDOI

Double Cache Approach with Wireless Technology for Preserving User Privacy

TL;DR: This article proposes a new method, known as “Double Cache Approach”, which uses a pair of caches to reduce the vulnerability of trust between users or third party and offers a vast improvement in privacy and security of user data in healthcare and other applications that use LBS.
References
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Proceedings ArticleDOI

Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking

TL;DR: A middleware architecture and algorithms that can be used by a centralized location broker service that adjusts the resolution of location information along spatial or temporal dimensions to meet specified anonymity constraints based on the entities who may be using location services within a given area.
Book

Privacy and Freedom

Westin Af
Journal ArticleDOI

Privacy and Freedom

Proceedings ArticleDOI

The new Casper: query processing for location services without compromising privacy

TL;DR: Zhang et al. as mentioned in this paper presented Casper1, a new framework in which mobile and stationary users can entertain location-based services without revealing their location information, which consists of two main components, the location anonymizer and the privacy-aware query processor.
Journal ArticleDOI

Privacy and Freedom

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