Privacy preserving in indoor fingerprint localization and radio map expansion

People spend most of their life time in indoor environments and in all of these environments, Location Service Providers (LSPs) improve users’ navigation. Preserving privacy in Location Based Services (LBSs) is vital for indoor LBSs and fingerprinting based indoor localization method is an emerging technique in indoor localization. In such systems, LSP may be curious and untrusted. Therefore, it is preferred that user estimates its location by using a Partial Radio Map (PRM) which is achieved by LSP, anonymously. In this paper, a privacy preserving method that uses Bloom filter for preserving anonymity and creating PRM during localization process, is proposed. In this method, LSP cannot recognize user identity, which is anonymized by the anonymizer. The proposed method has lower computational complexity compared with methods that use encryption or clustering concepts. The proposed method also has higher accuracy in localization compared with those that use Bloom filter with one random selected AP. Then, in order to decrease the complexity and to increase the accuracy at the same time, we introduce a method that expands the radio map by authenticated users, without compromising their privacy. We also enhance the performance of this method, using Hilbert curve for preserving the ambiguity of users’ location. After verifying the user’s data, LSP sends a certificate to the authenticated users. This certificate can increase the priority of users in LBS requests. Simulation results and measurements show that the proposed method on average improves the localization accuracy up to 16% compared with existing location privacy methods

Privacy in Indoor Positioning Systems: A Systematic Review

Ponència presentada a 10th International Conference on Localization and GNSS (ICL-GNSS), celebrada a Tampere (Finland) del 2 al 4 de juny de 2020This article presents a systematic review of privacy in indoor positioning systems. The selected 41 articles on location privacy preserving mechanisms employ non-inherently private methods such as encryption, k-anonymity, and differential privacy. The 15 identified mechanisms are categorized and summarized by where they are processed: on device, during transmission, or at a server. Trade-offs such as calculation speed, granularity, or complexity in set-up are identified for each mechanism. In 40% of the papers, some trade-offs are minimized by combining several methods into a hybrid solution. The combinations of mechanisms and their levels of offered privacy are suggested based on a series of user mobility cases

Privacy protection in location based services

This thesis takes a multidisciplinary approach to understanding the characteristics of Location Based Services (LBS) and the protection of location information in these transactions. This thesis reviews the state of the art and theoretical approaches in Regulations, Geographic Information Science, and Computer Science. Motivated by the importance of location privacy in the current age of mobile devices, this thesis argues that failure to ensure privacy protection under this context is a violation to human rights and poses a detriment to the freedom of users as individuals. Since location information has unique characteristics, existing methods for protecting other type of information are not suitable for geographical transactions. This thesis demonstrates methods that safeguard location information in location based services and that enable geospatial analysis. Through a taxonomy, the characteristics of LBS and privacy techniques are examined and contrasted. Moreover, mechanisms for privacy protection in LBS are presented and the resulting data is tested with different geospatial analysis tools to verify the possibility of conducting these analyses even with protected location information. By discussing the results and conclusions of these studies, this thesis provides an agenda for the understanding of obfuscated geospatial data usability and the feasibility to implement the proposed mechanisms in privacy concerning LBS, as well as for releasing crowdsourced geographic information to third-parties

Advanced Location-Based Technologies and Services

Since the publication of the first edition in 2004, advances in mobile devices, positioning sensors, WiFi fingerprinting, and wireless communications, among others, have paved the way for developing new and advanced location-based services (LBSs). This second edition provides up-to-date information on LBSs, including WiFi fingerprinting, mobile computing, geospatial clouds, geospatial data mining, location privacy, and location-based social networking. It also includes new chapters on application areas such as LBSs for public health, indoor navigation, and advertising. In addition, the chapter on remote sensing has been revised to address advancements

Privacy in trajectory micro-data publishing : a survey

We survey the literature on the privacy of trajectory micro-data, i.e., spatiotemporal information about the mobility of individuals, whose collection is becoming increasingly simple and frequent thanks to emerging information and communication technologies. The focus of our review is on privacy-preserving data publishing (PPDP), i.e., the publication of databases of trajectory micro-data that preserve the privacy of the monitored individuals. We classify and present the literature of attacks against trajectory micro-data, as well as solutions proposed to date for protecting databases from such attacks. This paper serves as an introductory reading on a critical subject in an era of growing awareness about privacy risks connected to digital services, and provides insights into open problems and future directions for research.Comment: Accepted for publication at Transactions for Data Privac

Location Estimation Methods for Open, Privacy Preserving Mobile Positioning

The future is mobile and location aware. More and more of our gadgets are portable and have an online presence. For our location-aware mobile future to be safe, we need to demand that our privacy and anonymity be protected. Currently, each and every location aware-system or feature requires us to give new people, corporations and entities access to one of our most intimate attributes, our location. The main solutions to ameliorate this have been by cloaking or hiding users from service providers or by moving trust to other "more trustable" parties. We want to minimize the need for trust. Your location is your own, and you should not have to pay with your privacy to determine it. Our focus lies on location estimation services - services that calculate your location based on measurements done on your network equipment - as they are the main drive behind the location-aware future. You can freely choose, discriminate against, and cloak yourself from services asking for your location, whereas removing the ability to determine your own location effectively impedes location awareness. We are interested in producing a freely available, open source, privacy preserving, community sourced, and safe location estimation service that minimizes the need for trust. In this thesis we focus on three things: Designing such a system, testing different ways of estimating locations, and determining the best way of estimating locations for the designed system

Privacy-preserving spatiotemporal multicast for mobile information services

Mobile devices have become essential for accessing information services anywhere at any time. While the so-called geographic multicast (geocast) has been considered in detail in existing research, it only focuses on delivering messages to all mobile devices that are currently residing within a certain geographic area. This thesis extends this notion by introducing a Spatiotemporal Multicast (STM), which can informally be described as a "geocast into the past". Instead of addressing users based on their current locations, this concept relates to the challenge of sending a message to all devices that have resided within a geographic area at a certain time in the past. While a wide variety of applications can be envisioned for this concept, it presents several challenges to be solved. In order to deliver messages to all past visitors of a certain location, an STM service would have to fully track all user movements at all times. However, collecting this kind of information is not desirable considering the underlying privacy implications, i.e., users may not wish to be identified by the sender of a message as this can disclose sensitive personal information. Consequently, this thesis aims to provide a privacy-preserving notion of STM. In order to realize such a service, this work first presents a detailed overview of possible applications. Based on those, functional, non-functional, as well as security and privacy objectives are proposed. These objectives provide the foundation for an in-depth literature review of potential mechanisms for realizing an STM service. Among the suggested options, the most promising relies on Rendezvous Points (RPs) for datagram delivery. In simple terms, RPs represent "anonymous mailboxes" that are responsible for certain spatiotemporal regions. Messages are deposited at RPs so that users can retrieve them later on. Protecting the privacy of users then translates to obfuscating the responsibilities of RPs for specific spatiotemporal regions. This work proposes two realizations: CSTM, which relies on cryptographic hashing, and OSTM, which considers the use of order-preserving encryption in a CAN overlay. Both approaches are evaluated and compared in detail with respect to the given objectives. While OSTM yields superior performance-related properties, CSTM provides an increased ability of protecting the privacy of users.Mobilgeräte bilden heute die Grundlage allgegenwärtiger Informationsdienste. Während der sogenannte geografische Multicast (Geocast) hier bereits ausführlich erforscht worden ist, so bezieht sich dieser nur auf Geräte, welche sich aktuell innerhalb einer geografischen Zielregion befinden. Diese Arbeit erweitert dieses Konzept durch einen räumlich-zeitlichen Multicast, welcher sich informell als "Geocast in die Vergangenheit" beschreiben lässt. Dabei wird die Zustellung einer Nachricht an alle Nutzer betrachtet, die sich in der Vergangenheit an einem bestimmten Ort aufgehalten haben. Während eine Vielzahl von Anwendungen für dieses Konzept denkbar ist, so ergeben sich hier mehrere Herausforderungen. Um Nachrichten an ehemalige Besucher eines Ortes senden zu können, müsste ein räumlich-zeitlicher Multicast-Dienst die Bewegungen aller Nutzer vollständig erfassen. Aus Gründen des Datenschutzes ist das zentralisierte Sammeln solch sensibler personenbezogener Daten jedoch nicht wünschenswert. Diese Arbeit befasst sich daher insbesondere mit dem Schutz der Privatsphäre von Nutzern eines solchen Dienstes. Zur Entwicklung eines räumlich-zeitlichen Multicast-Dienstes erörtert diese Arbeit zunächst mögliche Anwendungen. Darauf aufbauend werden funktionale, nicht-funktionale, sowie Sicherheits- und Privatsphäre-relevante Anforderungen definiert. Diese bilden die Grundlage einer umfangreichen Literaturrecherche relevanter Realisierungstechniken. Der vielversprechendste Ansatz basiert hierbei auf der Hinterlegung von Nachrichten in sogenannten Rendezvous Points. Vereinfacht betrachtet stellen diese "anonyme Briefkästen" für bestimmte räumlich-zeitliche Regionen dar. Nachrichten werden in diesen so hinterlegt, dass legitime Empfänger sie dort später abholen können. Der Schutz der Nutzer-Privatsphäre entspricht dann der Verschleierung der Zuständigkeiten von Rendezvous Points für verschiedene räumlich-zeitliche Regionen. Diese Arbeit schlägt zwei Ansätze vor: CSTM, welches kryptografische Hashfunktionen nutzt, sowie OSTM, welches ordnungserhaltende Verschlüsselung in einem CAN Overlay einsetzt. Beide Optionen werden detailliert analytisch sowie empirisch bezüglich ihrer Diensteigenschaften untersucht und verglichen. Dabei zeigt sich, dass OSTM vorteilhaftere Leistungseigenschaften besitzt, während CSTM einen besseren Schutz der Nutzer-Privatsphäre bietet