When Whereabouts is No Longer Thereabouts:Location Privacy in Wireless Networks

Modern mobile devices are fast, programmable and feature localization and wireless capabilities. 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 composed 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 important aspects of location privacy: location privacy threats, location-privacy preserving mechanisms, and privacy-preservation in pervasive social networks. Considering the recent surge of mobile applications, we begin by investigating location privacy threats of location-based services. We push further the understanding of the privacy risk by identifying the type and quantity of location information that statistically reveals users' identities and points of interest to third parties. Our results indicate that users are at risk even if they access location-based services episodically. This highlights the need to design privacy into location-based services. In the second part of this thesis, we delve into the subject of privacy-preserving mechanisms for mobile ad hoc networks. First, we evaluate a privacy architecture that relies on the concept of mix zones to engineer anonymity sets. Second, we identify the need for protocols to coordinate the establishment of mix zones and design centralized and distributed approaches. Because individuals may have different privacy requirements, we craft a game-theoretic model of location privacy to analyze distributed protocols. This model predicts strategic behavior of rational devices that protects their privacy at a minimum cost. This prediction leads to the design of efficient privacy-preserving protocols. Finally, we develop a dynamic model of interactions between mobile devices in order to analytically evaluate the level of privacy provided by mix zones. Our results indicate the feasibility and limitations of privacy protection based on mix zones. In the third part, we extend the communication model of mobile ad hoc networks to explore social aspects: users form groups called "communities" based on interests, proximity, or social relations and rely on these communities to communicate and discover their context. We analyze using challenge-response methodology the privacy implications of this new communication primitive. Our results indicate that, although repeated interactions between members of the same community leak community memberships, it is possible to design efficient schemes to preserve privacy in this setting. This work is part of the recent trend of designing privacy protocols to protect individuals. In this context, the author hopes that the results obtained, with both their limitations and their promises, will inspire future work on the preservation of privacy

Analyzing and Modeling Special Offer Campaigns in Location-based Social Networks

The proliferation of mobile handheld devices in combination with the technological advancements in mobile computing has led to a number of innovative services that make use of the location information available on such devices. Traditional yellow pages websites have now moved to mobile platforms, giving the opportunity to local businesses and potential, near-by, customers to connect. These platforms can offer an affordable advertisement channel to local businesses. One of the mechanisms offered by location-based social networks (LBSNs) allows businesses to provide special offers to their customers that connect through the platform. We collect a large time-series dataset from approximately 14 million venues on Foursquare and analyze the performance of such campaigns using randomization techniques and (non-parametric) hypothesis testing with statistical bootstrapping. Our main finding indicates that this type of promotions are not as effective as anecdote success stories might suggest. Finally, we design classifiers by extracting three different types of features that are able to provide an educated decision on whether a special offer campaign for a local business will succeed or not both in short and long term.Comment: in The 9th International AAAI Conference on Web and Social Media (ICWSM 2015

Virtual Location-Based Services: Merging the Physical and Virtual World

Location-based services gained much popularity through providing users with helpful information with respect to their current location. The search and recommendation of nearby locations or places, and the navigation to a specific location are some of the most prominent location-based services. As a recent trend, virtual location-based services consider webpages or sites associated with a location as 'virtual locations' that online users can visit in spite of not being physically present at the location. The presence of links between virtual locations and the corresponding physical locations (e.g., geo-location information of a restaurant linked to its website), allows for novel types of services and applications which constitute virtual location-based services (VLBS). The quality and potential benefits of such services largely depends on the existence of websites referring to physical locations. In this paper, we investigate the usefulness of linking virtual and physical locations. For this, we analyze the presence and distribution of virtual locations, i.e., websites referring to places, for two Irish cities. Using simulated tracks based on a user movement model, we investigate how mobile users move through the Web as virtual space. Our results show that virtual locations are omnipresent in urban areas, and that the situation that a user is close to even several such locations at any time is rather the normal case instead of the exception

Geo-Spotting: Mining Online Location-based Services for Optimal Retail Store Placement

The problem of identifying the optimal location for a new retail store has been the focus of past research, especially in the field of land economy, due to its importance in the success of a business. Traditional approaches to the problem have factored in demographics, revenue and aggregated human flow statistics from nearby or remote areas. However, the acquisition of relevant data is usually expensive. With the growth of location-based social networks, fine grained data describing user mobility and popularity of places has recently become attainable. In this paper we study the predictive power of various machine learning features on the popularity of retail stores in the city through the use of a dataset collected from Foursquare in New York. The features we mine are based on two general signals: geographic, where features are formulated according to the types and density of nearby places, and user mobility, which includes transitions between venues or the incoming flow of mobile users from distant areas. Our evaluation suggests that the best performing features are common across the three different commercial chains considered in the analysis, although variations may exist too, as explained by heterogeneities in the way retail facilities attract users. We also show that performance improves significantly when combining multiple features in supervised learning algorithms, suggesting that the retail success of a business may depend on multiple factors.Comment: Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, Chicago, 2013, Pages 793-80

Mobile Location Based Services for Mountaineering

Smart phones are widely accepted and popular with navigation and route guidance functionality becoming a standard feature. Locations based services, henceforth referred to as LBS in this document, are used in various contexts and are becoming more accessible with the wide adoption of mobile smart phones. Industry experts expect that Location based services to be a major success and will account for large market share and profits in mobile services. Service providers in this area are coming up with innovative services trying to grab a share in this potential area. On the other hand, there is also some pessimism on the pace at which LBS taking-off in practice due to various reasons. For any service or business to be successful it should create value to the end-users. There are many key players involved to make LBS realizable and providing value, which include technology providers, service providers, telecom companies, regulation and standardization bodies and end-users. This thesis is a literature review of LBS and its general applications in real world with emphasis on its use in mountaineering. Scope of this literature review is to study the components of LBS, its architecture, positioning techniques, general application area, established standards and potential business model. While emphasizing LBS use in mountaineering, a concluded LBS demo project for mountaineering, sponsored by Eu-ropean Commission, called PARAMOUNT (Public Safety & Commercial Info-Mobility Applications & Services in the Mountains) is taken as reference. From business pers-pective, a conceptual business model called STOF (Service, Technology, Organization and Finance) model is used to analyze PARAMOUNT. /Kir1