A Collaborative Protocol for Private Retrieval of Location-Based Information

Privacy and security are paramount for the proper deployment of location-based services (LBSs). We present a novel protocol based on user collaboration to privately retrieve location-based information from an LBS provider. Our approach neither assumes that users or the LBS can be completely trusted with regard to privacy, nor relies on a trusted third party. In addition, user queries, containing accurate locations, remain unchanged, and the collaborative protocol does not impose any special requirements on the query-response function of the LBS. The protocol is analyzed in terms of privacy, network traffic, and LBS processing overhead. We show that our proposal provides exponential scalability in the probability of guaranteed privacy breach, at the expense of a linear relative network cost.Preprin

Decentralized collaborative TTP free approach for privacy preservation in location based services

In recent trends, growth of location based services have been increased due to the large usage of cell phones, personal digital assistant and other devices like location based navigation, emergency services, location based social networking, location based advertisement, etc. Users are provided with important information based on location to the service provider that results the compromise with their personal information like user’s identity, location privacy etc. To achieve location privacy of the user, cryptographic technique is one of the best technique which gives assurance. Location based services are classified as Trusted Third Party (TTP) & without Trusted Third Party that uses cryptographic approaches. TTP free is one of the prominent approach in which it uses peer-to-peer model. In this approach, important users mutually connect with each other to form a network to work without the use of any person/server. There are many existing approaches in literature for privacy preserving location based services, but their solutions are at high cost or not supporting scalability.  In this paper, our aim is to propose an approach along with algorithms that will help the location based services (LBS) users to provide location privacy with minimum cost and improve scalability

Privacy Preserving Location-Based Client-Server Service Using Standard Cryptosystem

Location-Based Mobile Services (LBMS) is rapidly gaining ground and becoming increasingly popular, because of the variety of efficient and personalized services it offers. However, if users are not guaranteed their privacy and there is no assurance of genuineness of server\u27s response, the use of these services would be rendered useless and could deter its growth in mobile computing. This paper aims to provide confidentiality and integrity for communication that occurs between users and location service providers. A practical system that guarantees a user\u27s privacy and integrity of server\u27s response, using a cryptographic scheme with no trusted intermediary, is provided. This scheme also employs the use of symmetric and asymmetric encryption algorithms to ensure secure message and key transfer. In order to overcome the problem of computational complexities with these algorithms, AES-256 is used to encrypt the message and user\u27s location. Several researches have been done in this category but there is still no system that checks the integrity of server\u27s response. The proposed scheme is resistant to a range of susceptible attacks, because it provides a detailed security analysis and, when compared with related work, shows that it can actually guarantee privacy and integrity with faster average response time and higher throughput in LBMS

Location Privacy for Mobile Crowd Sensing through Population Mapping

Opportunistic sensing allows applications to “task” mobile devices to measure context in a target region. For example, one could leverage sensor-equipped vehicles to measure traffic or pollution levels on a particular street or users\u27 mobile phones to locate (Bluetooth-enabled) objects in their vicinity. In most proposed applications, context reports include the time and location of the event, putting the privacy of users at increased risk: even if identifying information has been removed from a report, the accompanying time and location can reveal sufficient information to de-anonymize the user whose device sent the report. We propose and evaluate a novel spatiotemporal blurring mechanism based on tessellation and clustering to protect users\u27 privacy against the system while reporting context. Our technique employs a notion of probabilistic k-anonymity; it allows users to perform local blurring of reports efficiently without an online anonymization server before the data are sent to the system. The proposed scheme can control the degree of certainty in location privacy and the quality of reports through a system parameter. We outline the architecture and security properties of our approach and evaluate our tessellation and clustering algorithm against real mobility traces

Privacy in Mobile Computing for Location-Sharing-Based Services

Location-Sharing-Based Services (LSBS) complement Location-Based Services by using locations from a group of users, and not just individuals, to provide some contextualized service based on the locations in the group. However, there are growing concerns about the misuse of location data by third-parties, which fuels the need for more privacy controls in such services. We address the relevant problem of privacy in LSBSs by providing practical and effective solutions to the privacy problem in one such service, namely the fair rendez-vous point (FRVP) determination service. The privacy preserving FRVP (PPFRVP) problem is general enough and nicely captures the computations and privacy requirements in LSBSs. In this paper, we propose two privacy-preserving algorithms for the FRVP problem and analytically evaluate their privacy in both passive and active adversarial scenarios. We study the practical feasibility and performance of the proposed approaches by implementing them on Nokia mobile devices. By means of a targeted user-study, we attempt to gain further understanding of the popularity, the privacy and acceptance of the proposed solutions

"Once Upon a Place": Compute Your Meeting Location Privately

Popular services such as Doodle Mobile and Tymelie are extremely useful planning tools that enable mobile-phone users to determine common meeting time(s) for events. Similar planning tools for determining optimal meeting locations, based on the location preferences of the users, are highly desirable for event planning and management in popular mobile phone applications, such as taxi sharing, route planning and mobile participatory sensing. Yet, they have received very little attention by researchers. An important, and often overlooked, facet of such planning applications is the privacy of the participating users and their preferences; users want to agree on a meeting location without necessarily revealing their location preferences to the service provider or to the other users. In this paper, we address the problem of privacy-preserving optimal meeting-location computation, especially focusing on its applicability to current mobile devices and applications. We first define the notion of privacy in such computations. Second, we model the problem of optimal meeting-location computation as a privacy-preserving k-center problem and we design two solutions; both solutions take advantage of the homomorphic properties of well-known cryptosystems by Boneh-Goh-Nissim, ElGamal and Paillier in order to perform oblivious computations. Third, we implement the proposed solutions on a testbed of the latest generation Nokia mobile devices and study their performance. Finally, we assess the utility and expectations, in terms of privacy and usability, of the proposed solutions by means of a targeted survey and user-study of mobile-phone users

The Theory and Application of Privacy-preserving Computation

Privacy is a growing concern in the digital world as more information becomes digital every day. Often the implications of how this information could be exploited for nefarious purposes are not explored until after the fact. The public is becoming more concerned about this. This dissertation introduces a new paradigm for tackling the problem, namely, transferable multiparty computation (T-MPC). T-MPC builds upon existing multiparty computation work yet allows some additional flexibility in the set of participants. T-MPC is orders of magnitude more efficient for certain applications. This greatly increases the scalability of the sizes of networks supported for privacy-preserving computation

Contributions to privacy protection for ubiquitous computing

El desenvolupament de noves tecnologies ha introduït el concepte de Computació Ubiqua, a on els objectes que ens envolten poden tenir processadors integrats i establir la comunicació amb altres sistemes, amb la finalitat d'oferir serveis personalitzats per ajudar-nos amb les nostres tasques habituals. No obstant això, a causa de que és possible tenir ordinadors en gairebé qualsevol lloc o objecte, això ha obert noves discussions sobre temes tals com la privadesa i la seguretat, considerats des de diferents punts de vista, com el desenvolupaments jurídics, socials, econòmics i tecnològics, amb una importància cada vegada major al món actual. En aquesta tesi discutim i analitzem algunes de les principals qüestions de seguretat i privadesa a les tecnologies actuals, tals com a telèfons intel·ligents, dispositius RFID o ciutats intel·ligents, i proposem alguns protocols per fer front a aquests temes garantint la privadesa dels usuaris a tot moment.El desarrollo de nuevas tecnologías ha introducido el concepto de Computación Ubicua , en donde los objetos que nos rodean pueden tener procesadores integrados y establecer la comunicación con otros sistemas, con el fin de ofrecer servicios personalizados para ayudarnos con nuestras tareas habituales. Sin embargo, debido a que es posible tener ordenadores en casi cualquier lugar u objeto, esto ha abierto nuevas discusiones sobre temas tales como la privacidad y la seguridad, considerado desde diferentes puntos de vista, como el desarrollos jurídicos, sociales, económicos y tecnológicos, con una importancia cada vez mayor en el mundo actual. En esta tesis discutimos y analizamos algunas de las principales cuestiones de seguridad y privacidad en las tecnologías actuales, tales como teléfonos inteligentes, dispositivos RFID o ciudades inteligentes, y proponemos algunos protocolos para hacer frente a estos temas garantizando la privacidad de los usuarios en todo momento.The development of new technologies has introduced the concept of Ubiquitous Computing, whereby the objects around us can have an embedded computer and establish communications with each other, in order to provide personalized services to assist with our tasks. However, because it is possible to have computers almost anywhere and within any object, this has opened up new discussions on issues such as privacy and security, considered from many different views, such as the legal, social, economic and technological development perspectives, all taking an increasingly significant importance in today’s world. In this dissertation we discuss and analyze some of the main privacy and security issues in current technologies, such as smartphones, RFIDs or smart cities, and we propose some protocols in order to face these issues guarantying users' privacy anytime