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40
Friendship-based location privacy in Mobile Social Networks
"... Abstract: Location privacy in Mobile Social Networks (MSNs) has generated significant interest in recent years, with many proposed methods to address the problem. Commercial solutions to this problem have suggested designing better ways for users to determine when to report their locations, while ac ..."
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Abstract: Location privacy in Mobile Social Networks (MSNs) has generated significant interest in recent years, with many proposed methods to address the problem. Commercial solutions to this problem have suggested designing better ways for users to determine when to report their locations, while academic researchers have proposed solutions that involve deploying trusted third party servers to protect user privacy. In this paper, we showed that simply omitting location updates does not provide adequate privacy protections, especially in situations where the friendship relationships between users are known. We proposed a fake location update algorithm that allows a user to protect his privacy. A key feature of our approach is that it can be adopted without the use of any third party services, making them more practical. We evaluate our approach using extensive simulation experiments.
Privacy-Friendly Business Models for Location-Based Mobile Services
"... www.jtaer.com DOI: 10.4067/S0718-18762011000200009 ..."
Tracking Games in Mobile Networks
"... Abstract. Users of mobile networks can change their identifier in regions called mix zones in order to defeat the tracking of their location by third parties. Mix zones must be carefully deployed in the network to reduce the cost induced on mobile users and to provide high location privacy. Unlike m ..."
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Abstract. Users of mobile networks can change their identifier in regions called mix zones in order to defeat the tracking of their location by third parties. Mix zones must be carefully deployed in the network to reduce the cost induced on mobile users and to provide high location privacy. Unlike most previous work that considers a global adversary, we consider a local adversary equipped with multiple eavesdropping stations. We study the interaction between the local adversary deploying eavesdropping stations to track mobile users and mobile users deploying mix zones to protect their location privacy. We use a game-theoretic model to predict the strategies of both players. We derive the strategies at equilibrium in complete and incomplete information scenarios and propose an algorithm to compute the equilibrium. Finally, based on real road traffic information, we numerically quantify the effect of complete and incomplete information on the strategies of mobile users and of the adversary. In complete information scenarios, mobile users and the adversary tend to adopt complementary strategies: users place mix zones where there is no eavesdropping station, and vice versa. In incomplete information scenarios, the location privacy level achieved by mobile users depends on their level of uncertainty about the strategy of the adversary. 1
Collaborative Location Privacy with Rational Users
"... Abstract. Recent smartphones incorporate embedded GPS devices that enable users to obtain geographic information about their surroundings by providing a location-based service (LBS) with their current coordinates. However, LBS providers collect a significant amount of data from mobile users and coul ..."
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Abstract. Recent smartphones incorporate embedded GPS devices that enable users to obtain geographic information about their surroundings by providing a location-based service (LBS) with their current coordinates. However, LBS providers collect a significant amount of data from mobile users and could be tempted to misuse it, by compromising a customer’s location privacy (her ability to control the information about her past and present location). Many solutions to mitigate this privacy threat focus on changing both the architecture of location-based systems and the business models of LBS providers. MobiCrowd does not introduce changes to the existing business practices of LBS providers, rather it requires mobile devices to communicate wirelessly in a peer-to-peer fashion. To lessen the privacy loss, users seeking geographic information try to obtain this data by querying neighboring nodes, instead of connecting to the LBS. However, such a solution will only function if users are willing to share regional data obtained from the LBS provider. We model this collaborative location-data sharing problem with rational agents following threshold strategies. Initially, we study agent cooperation by using pure game theory and then by combining game theory with an epidemic model that is enhanced to support threshold strategies to address a complex multi-agent scenario. From our game-theoretic analysis, we derive cooperative and non-cooperative Nash equilibria and the optimal threshold that maximizes agents ’ expected utility. 1
Selective location blinding using hash chains
- In Proc. 19th Workshop in Security Protocols, LNCS 7114
, 2011
"... Abstract. Location-based applications require a user’s movements and positions to provide customized services. However, location is a sensitive piece of information that should not be revealed unless strictly neces-sary. In this paper we propose a procedure that allows a user to control the precisio ..."
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Abstract. Location-based applications require a user’s movements and positions to provide customized services. However, location is a sensitive piece of information that should not be revealed unless strictly neces-sary. In this paper we propose a procedure that allows a user to control the precision in which his location information is exposed to a service provider, while allowing his location to be certified by a location ver-ifier. Our procedure makes use of a hash chain to certify the location information in such a way that the hashes of the chain correspond to an increasing level of precision. 1
Time Warp: How Time Affects Privacy in LBSs
"... Abstract. Location Based Services (LBSs) introduce several privacy issues, the most relevant ones being: (i) how to anonymize a user; (ii) how to specify the level of anonymity; and, (iii) how to guarantee to a given user the same level of desired anonymity for all of his requests. Anonymizing the u ..."
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Abstract. Location Based Services (LBSs) introduce several privacy issues, the most relevant ones being: (i) how to anonymize a user; (ii) how to specify the level of anonymity; and, (iii) how to guarantee to a given user the same level of desired anonymity for all of his requests. Anonymizing the user within k potential users is a common solution to (i). A recent work [28] highlighted how specifying a practical value of k could be a difficult choice for the user, hence introducing a feeling based model: a user defines the desired level of anonymity specifying a given area (e.g. a shopping mall). The proposal sets the level of anonymity (ii) as the popularity of the area—popularity being measured via the entropy of the footprints of the visitors in that area. To keep the privacy level constant (iii), the proposal conceals the user requests always within an area of the same popularity—independently from the current user’s position. The main contribution of this work is to highlight the importance of the time when providing privacy in LBSs. Further, we show how applying our considerations user privacy can be violated in the related model, but also in a relaxed one. We support our claim with both analysis and a practical counter-example.
Game Theoretic Analysis of Multiparty Access Control in Online Social Networks
"... Existing online social networks (OSNs) only allow a single user to restrict access to her/his data but cannot provide any mechanism to enforce privacy concerns over data associated with multiple users. This situation leaves privacy conflicts largely unresolved and leads to the potential disclosure o ..."
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Existing online social networks (OSNs) only allow a single user to restrict access to her/his data but cannot provide any mechanism to enforce privacy concerns over data associated with multiple users. This situation leaves privacy conflicts largely unresolved and leads to the potential disclosure of users ’ sensitive information. To ad-dress such an issue, a MultiParty Access Control (MPAC) model was recently proposed, including a systematic approach to iden-tify and resolve privacy conflicts for collaborative data sharing in OSNs. In this paper, we take another step to further study the prob-lem of analyzing the strategic behavior of rational controllers in multiparty access control, where each controller aims to maximize her/his own benefit by adjusting her/his privacy setting in collab-orative data sharing in OSNs. We first formulate this problem as a multiparty control game and show the existence of unique Nash Equilibrium (NE) which is critical because at an NE, no controller has any incentive to change her/his privacy setting. We then present algorithms to compute the NE and prove that the system can con-verge to the NE in only a few iterations. A numerical analysis is also provided for different scenarios that illustrate the interplay of controllers in the multiparty control game. In addition, we con-duct user studies of the multiparty control game to explore the gap between game theoretic approaches and real human behaviors.
This dissertation, “Security, Privacy and Applications in Vehicular Ad Hoc Networks,”
, 2012
"... MICHIGAN TECHNOLOGICAL UNIVERSITY 2012 ..."
PAR
, 2011
"... Modern mobile devices are fast, programmable and feature localization and wireless capabil-ities. These technological advances notably facilitate mobile access to Internet, development of mobile applications and sharing of personal information, such as location information. Cell phone users can for ..."
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Modern mobile devices are fast, programmable and feature localization and wireless capabil-ities. These technological advances notably facilitate mobile access to Internet, development of mobile applications and sharing of personal information, such as location information. Cell phone users can for example share their whereabouts with friends on online social networks. Following this trend, the field of ubiquitous computing foresees communication networks com-posed of increasingly inter-connected wireless devices offering new ways to collect and share information in the future. It also becomes harder to control the spread of personal information. Privacy is a critical challenge of ubiquitous computing as sharing personal information exposes users ’ private lives. Traditional techniques to protect privacy in wired networks may be inadequate in mobile networks because users are mobile, have short-lived encounters and their communications can be easily eavesdropped upon. These characteristics introduce new privacy threats related to location information: a malicious entity can track users ’ whereabouts and learn aspects of users ’ private lives that may not be apparent at first. In this dissertation, we focus on three
A Structure of Adaptive Portable Video Streaming and Efficient Common Video Cassette Sharing In the Clouds
"... ABSTRACT: Utilizing the reasoning processing technology, a new cellular movie loading structure, known as AMESCloud, which has two main parts: AMoV (adaptive cellular movie streaming) and ESoV (efficient public movie sharing). AMoV and ESoV build a personal broker to offer movie loading services ef ..."
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ABSTRACT: Utilizing the reasoning processing technology, a new cellular movie loading structure, known as AMESCloud, which has two main parts: AMoV (adaptive cellular movie streaming) and ESoV (efficient public movie sharing). AMoV and ESoV build a personal broker to offer movie loading services efficiently for each cellular customer. For a given customer, AMoV lets her undercover broker adaptively adjust her stream flow with a scalable movie programming technique in accordance with the reviews of link quality. Likewise, ESoV watches the online community communications among cellular users, and their personal providers try to prefetch movie content in advance. We apply a model of the AMES-Cloud structure to show its performance. It is shown that the personal providers in the atmosphere can effectively offer the flexible loading, and perform movie discussing (i.e., prefetching) in accordance with the online community analysis.. We first recommend an precise Comparison-based Profile Related method (eCPM) which runs between two parties, an initiator and a -responder. The eCPM enable the initiator to acquire the comparison-based matching outcome about a specified feature in their profiles, while stop their feature values from exposure. We then recommend an implied Comparison-based Profile Related method (iCPM) which allows the initiator to straight acquire some information instead of the evaluation outcome from the -responder. The information unique to customer profile can be separated into multiple groups by the -responder. The initiator unquestioningly selects the involved category which is unknown to the -responder.