text: Real-time crowdsourced maps such as Waze provide timely updates on traffic, congestion, accidents and points of interest. In this paper, we demonstrate how lack of strong location authentication allows creation of software-based Sybil devices that expose crowdsourced map systems to a variety of security and privacy attacks. Our experiments show that a single Sybil device with limited resources can cause havoc on Waze, reporting false congestion and accidents and automatically rerouting user traffic. More importantly, we describe techniques to generate Sybil devices at scale, creating armies of virtual vehicles capable of remotely tracking precise movements for large user populations while avoiding detection. We propose a new approach to defend against Sybil devices based on co-location edges , authenticated records that attest to the one-time physical co-location of a pair of devices. Over time, co-location edges combine to form large proximity graphs that attest to physical interactions between devices, allowing scalable detection of virtual vehicles. We demonstrate the efficacy of this approach using large-scale simulations, and discuss how they can be used to dramatically reduce the impact of attacks against crowdsourced mapping services.
  @cite_4: Conventional mobile social services such as Loopt and Google Latitude rely on two classes of trusted relationships: participants trust a centralized server to manage their location information and trust between users is based on existing social relationships. Unfortunately, these assumptions are not secure or general enough for many mobile social scenarios: centralized servers cannot always be relied upon to preserve data confidentiality, and users may want to use mobile social services to establish new relationships. To address these shortcomings, this paper describes SMILE, a privacy-preserving "missed-connections" service in which the service provider is untrusted and users are not assumed to have pre-established social relationships with each other. At a high-level, SMILE uses short-range wireless communication and standard cryptographic primitives to mimic the behavior of users in existing missed-connections services such as Craigslist: trust is founded solely on anonymous users' ability to prove to each other that they shared an encounter in the past. We have evaluated SMILE using protocol analysis, an informal study of Craigslist usage, and experiments with a prototype implementation and found it to be both privacy-preserving and feasible.
  @cite_33: Vehicular Ad Hoc Networks (VANETs) enable car-to-car communication without the support of network infrastructure, which introduce diverse application possibilities and have drawn much attention from academy and industry in the past years. Unlike other ad hoc networks, nodes in VANETs are restricted to move in streets and have limited communication ranges. Intuitively, vehicle-to-vehicle communication somehow has similarity to human-to-human interaction, which lead to an interesting question of exploring the social properties of VANET nodes. To address the question, we consider encounters of vehicles as their social relationships and model VANETs as social graphs. Based on the social graph model, we use two traces of mobile vehicles from San Francisco and Shanghai to explore their social properties. Our analysis show that several universal laws of social network are hold for VANETs. The social graphs forming by vehicles are scale-free networks with power-law like distribution of node degrees. Small world phenomenon is also observed in our experiments: the nodes in VANETs have high cluster coefficient and there exist short paths between node pairs less than 3 hops on average. The implication of our analytical results is of benefit to develop large scale software system for mobile applications such as VANETs, as well as helps to facilitate inter-device wireless communications in pervasive environment.
  @cite_7: Today's location-sensitive service relies on user's mobile device to determine the current location. This allows malicious users to access a restricted resource or provide bogus alibis by cheating on their locations. To address this issue, we propose A Privacy-Preserving LocAtion proof Updating System (APPLAUS) in which colocated Bluetooth enabled mobile devices mutually generate location proofs and send updates to a location proof server. Periodically changed pseudonyms are used by the mobile devices to protect source location privacy from each other, and from the untrusted location proof server. We also develop user-centric location privacy model in which individual users evaluate their location privacy levels and decide whether and when to accept the location proof requests. In order to defend against colluding attacks, we also present betweenness ranking-based and correlation clustering-based approaches for outlier detection. APPLAUS can be implemented with existing network infrastructure, and can be easily deployed in Bluetooth enabled mobile devices with little computation or power cost. Extensive experimental results show that APPLAUS can effectively provide location proofs, significantly preserve the source location privacy, and effectively detect colluding attacks.
  @cite_29: Location is rapidly becoming the next "killer application" as location-enabled mobile handheld devices proliferate. One class of applications that has yet-to-emerge are those in which users have an incentive to lie about their location. These applications cannot rely solely on the users' devices to discover and transmit location information because users have an incentive to cheat. Instead, such applications require their users to prove their locations. Unfortunately, today's mobile users lack a mechanism to prove their current or past locations. Consequently, these applications have yet to take off despite their potential. This paper presents location proofs - a simple mechanism that enables the emergence of mobile applications that require "proof" of a user's location. A location proof is a piece of data that certifies a receiver to a geographical location. Location proofs are handed out by the wireless infrastructure (e.g., a Wi-Fi access point or a cell tower) to mobile devices. The relatively short range of the wireless radios ensures that these devices are in physical proximity to the wireless transmitter. As a result, these devices are capable of proving their current or past locations to mobile applications. In this paper, we start by describing a mechanism to implement location proofs. We then present a set of six future applications that require location proofs to enable their core functionality.
  @cite_32: 
  @cite_56: Although location-based applications have existed for several years, verifying the correctness of a user's claimed location is a challenge that has only recently gained attention in the research community. Existing architectures for the generation and verification of such location proofs have limited flexibility. For example, they do not support the proactive gathering of location proofs, where, at the time of acquiring a location proof, a user does not yet know for which application or service she will use this proof. Supporting proactive location proofs is challenging because these proofs might enable proof issuers to track a user or they might violate a user's location privacy by revealing more information about a user's location than strictly necessary to an application. We present six essential design goals that a flexible location proof architecture should meet. Furthermore, we introduce a location proof architecture that realizes our design goals and that includes user anonymity and location privacy as key design components, as opposed to previous proposals. Finally, we demonstrate how some of the design goals can be achieved by adopting proper cryptographic techniques.
  @cite_34: 
  @cite_11: A trusted execution environment (TEE) is a secure, integrity-protected processing environment, consisting of processing, memory and storage capabilities. It is isolated from the “normal” processing environment, sometimes called the rich execution environment (REE), where the device operating system and applications run. TEEs can make it possible to build REE applications and services with better security and usability by partitioning them so that sensitive operations are restricted to the TEE and sensitive data, like cryptographic keys, never leave the TEE. In our daily lives, we encounter more and more services that use dedicated hardware tokens to improve their security: one-time code tokens for two-factor authentication, wireless tokens for opening doors in buildings or cars, tickets for public transport, and so on. Mobile devices equipped with TEEs have the potential for replacing these many tokens thereby improving the usability for users while also reducing the cost for the service providers without hampering security.
summary: Mobile Location Authentication. Defending against forged GPS is challenging. One direction is to authenticate user locations using wireless infrastructures: WiFi APs @cite_56 @cite_29 , cellular base stations @cite_56 @cite_29 and femtocells @cite_11 . Devices must come into physical proximity to these infrastructures to be authenticated. But it requires cooperation among a wide range of infrastructures (also modifications to their software hardware), which is impractical for large-scale services like Waze. Our work only uses a small number of trusted infrastructures to bootstrap, and relies on peer-based trust propagation to achieve coverage. Other researchers have proposed peer-based'' methods to authenticate collocated mobile devices @cite_32 @cite_33 @cite_7 @cite_4 @cite_34 . Different from existing work, we use peer-based collocation authentication to build proximity graphs for Sybil detection, instead of directly authenticating a device's physical location.