Myself: Local perturbation for location privacy in LBS applications.
01 Sep 2014-pp 1981-1985
TL;DR: This work considers location privacy techniques that work using obfuscation operators and provide different information services using different cloaking techniques without any trusted components other than the client's mobile device to provide different privacy levels.
Abstract: The location security in current location-based services (LBS) meets threat where mobile users have to report their actual location knowledge to the LBS provider in order to get their desired POI, (Points of Interests). We consider location privacy techniques that work using obfuscation operators and provide different information services using different cloaking techniques without any trusted components other than the client's mobile device. The techniques are then covered according to the random category. It blurs the accurate user location (i.e., a point with coordinates) and replaces it with a well-shaped cloaked region (e.g. Circle, Rectangle, Pentagon etc.). We have recommended the technique where instead of exchanging cloaking data with peers, user queries directly to LBS. We have presented techniques where first technique which provides different privacy levels using obfuscation operators. The second technique for query processing generates the region of different shapes. Third demonstrates regional cloaking and two more new ideas are presented. We have shown effectiveness and performance of these techniques.
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09 Jun 2008
TL;DR: This work proposes a novel framework to support private location-dependent queries, based on the theoretical work on Private Information Retrieval (PIR), which achieves stronger privacy for snapshots of user locations and is the first to provide provable privacy guarantees against correlation attacks.
Abstract: Mobile devices equipped with positioning capabilities (e.g., GPS) can ask location-dependent queries to Location Based Services (LBS). To protect privacy, the user location must not be disclosed. Existing solutions utilize a trusted anonymizer between the users and the LBS. This approach has several drawbacks: (i) All users must trust the third party anonymizer, which is a single point of attack. (ii) A large number of cooperating, trustworthy users is needed. (iii) Privacy is guaranteed only for a single snapshot of user locations; users are not protected against correlation attacks (e.g., history of user movement).We propose a novel framework to support private location-dependent queries, based on the theoretical work on Private Information Retrieval (PIR). Our framework does not require a trusted third party, since privacy is achieved via cryptographic techniques. Compared to existing work, our approach achieves stronger privacy for snapshots of user locations; moreover, it is the first to provide provable privacy guarantees against correlation attacks. We use our framework to implement approximate and exact algorithms for nearest-neighbor search. We optimize query execution by employing data mining techniques, which identify redundant computations. Contrary to common belief, the experimental results suggest that PIR approaches incur reasonable overhead and are applicable in practice.
830 citations
"Myself: Local perturbation for loca..." refers background in this paper
...Gabrial in [4], presented information retrieval based work of cloaking....
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TL;DR: An adversary model is introduced and an analysis of the proposed obfuscation operators is provided to evaluate their robustness against adversaries aiming to reverse the obfuscation effects to retrieve a location that better approximates the location of the users.
Abstract: The pervasive diffusion of mobile communication devices and the technical improvements of location techniques are fostering the development of new applications that use the physical position of users to offer location-based services for business, social, or informational purposes. In such a context, privacy concerns are increasing and call for sophisticated solutions able to guarantee different levels of location privacy to the users. In this paper, we address this problem and present a solution based on different obfuscation operators that, when used individually or in combination, protect the privacy of the location information of users. We also introduce an adversary model and provide an analysis of the proposed obfuscation operators to evaluate their robustness against adversaries aiming to reverse the obfuscation effects to retrieve a location that better approximates the location of the users. Finally, we present some experimental results that validate our solution.
246 citations
TL;DR: This work surveys recent advancements for the offering of K-anonymity in LBSs and presents some of the most prevalent approaches, which heavily depend on a trusted server component that acts as an intermediate between the end user and the service provider to preserve the anonymity of the former entity.
Abstract: The offering of anonymity in relational databases has attracted a great deal of attention in the database community during the last decade [4]. Among the different solution approaches that have been proposed to tackle this problem, K-anonymity has received increased attention and has been extensively studied in various forms. New forms of data that come into existence, like location data capturing user movement, pave the way for the offering of cutting edge services such as the prevailing Location Based Services (LBSs). Given that these services assume an in-depth knowledge of the mobile users' whereabouts it is certain that the assumed knowledge may breach the privacy of the users. Thus, concrete approaches are necessary to preserve the anonymity of the mobile users when requesting LBSs. In this work, we survey recent advancements for the offering of K-anonymity in LBSs. Most of the approaches that have been proposed heavily depend on a trusted server component -- that acts as an intermediate between the end user and the service provider - to preserve the anonymity of the former entity. Existing approaches are partitioned in three categories: (a) historical K-anonymity, (b) location K-anonymity, and (c) trajectory K-anonymity. In each of these categories we present some of the most prevalentmethodologies that have been proposed and highlight their operation.
106 citations
"Myself: Local perturbation for loca..." refers methods in this paper
...The methods in paper [3] shows that real locations are distorted which prevents the provider from learning private information of the users....
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...In [3],[8],[9], K-anonymity schemes are used which authors have used hybrid approach....
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TL;DR: The article's proposal, SpaceTwist, aims to offer location privacy for k nearest neighbor (kNN) queries at low communication cost without requiring a trusted anonymizer and is believed to be the first solution that expresses the server-side functionality in a single SQL statement.
Abstract: Users of mobile services wish to retrieve nearby points of interest without disclosing their locations to the services. This article addresses the challenge of optimizing the query performance while satisfying given location privacy and query accuracy requirements. The article's proposal, SpaceTwist, aims to offer location privacy for k nearest neighbor (kNN) queries at low communication cost without requiring a trusted anonymizer. The solution can be used with a conventional DBMS as well as with a server optimized for location-based services. In particular, we believe that this is the first solution that expresses the server-side functionality in a single SQL statement. In its basic form, SpaceTwist utilizes well-known incremental NN query processing on the server. When augmented with a server-side granular search technique, SpaceTwist is capable of exploiting relaxed query accuracy guarantees for obtaining better performance. We extend SpaceTwist with so-called ring ranking, which improves the communication cost, delayed termination, which improves the privacy afforded the user, and the ability to function in spatial networks in addition to Euclidean space. We report on analytical and empirical studies that offer insight into the properties of SpaceTwist and suggest that our proposal is indeed capable of offering privacy with very good performance in realistic settings.
60 citations
"Myself: Local perturbation for loca..." refers background in this paper
...In [2],[4],[6], private information retrieval is demonstrated where threat is central servers from where data is retrieved and sent to client....
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01 Jan 2008
TL;DR: The most relevant techniques for guaranteeing location privacy to LBS users are surveyed and the rigid dichotomy between schemes which rely on Trusted Third Parties (TTP-based) and those which do not (T TP-free) is emphasised.
Abstract: Location-Based Services (LBS) are gaining importance due to the advances in mobile networks and positioning technologies. Nevertheless, the wide deployment of LBS can jeopardise the privacy of their users, so ensuring user privacy is paramount to the success of those services. This article surveys the most relevant techniques for guaranteeing location privacy to LBS users. The rigid dichotomy between schemes which rely on Trusted Third Parties (TTP-based) and those which do not (TTP-free) is emphasised. Also, the convenience of both approaches is discussed and some ideas on the future of location privacy in these services are sketched.
58 citations
"Myself: Local perturbation for loca..." refers background or methods in this paper
...[I ],[2], papers discuss about classification and also shows drawback of centralised and trusted party based privacy schemes....
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...In another paper [2], classify under this category all the methods that do not distort the location of LBS users to protect their privacy....
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...In [2],[4],[6], private information retrieval is demonstrated where threat is central servers from where data is retrieved and sent to client....
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