Agusti Solanas, Antoni Martínez-Ballesté

Computer Communications 31 (6), 1181-1191

Description: Location-based services (LBS) will be a keystone of the new information society that is founded on the information and communi- cations technologies (ICTs). Mobile devices such as cell phones or laptops have become ubiquitous. They are equipped with a variety of localisation systems that make them proper for making use of the new LBS. Most of the times, these services are provided by a trusted company (e.g. a telecommunications company). However, the massive use of mobile devices pave the way for the creation of ad hoc wireless networks that can be used to exchange information based on locations. When the exchange of location information is done amongst untrusted parties, the privacy of the participants could be in jeopardy. In this paper we present a novel solution that guarantees the privacy of the users of LBS. Our technique is built up of several modules that progressively increase the privacy level of the users. Unlike the existing approaches, our proposal does not rely on a trusted third party (TTP) to anonymise the users and to guarantee their location privacy.

Fran Casino, Josep Domingo-Ferrer, Constantinos Patsakis, Domènec Puig, Agusti Solanas

Journal of Computer and System Sciences 81 (6), 1000-1011

Description: This article proposes a new technique for Privacy Preserving Collaborative Filtering (PPCF) based on microaggregation, which provides accurate recommendations estimated from perturbed data whilst guaranteeing user k-anonymity. The experimental results presented in this article show the effectiveness of the proposed technique in protecting users' privacy without compromising the quality of the recommendations. In this sense, the proposed approach perturbs data in a much more efficient way than other well-known methods such as Gaussian Noise Addition (GNA).

Agusti Solanas, Josep Domingo-Ferrer, Antoni Martínez-Ballesté, Vanesa Daza

Computer Networks 51 (9), 2268-2279

Description: The fast growth of Radio Frequency IDentification (RFID) implies a deployment challenge, namely how to keep this technology scalable without renouncing security and privacy features. This paper focuses on combining tag privacy and scalability using the hash locks mechanism. Our contribution is twofold: (i) a cell-based architecture is proposed in which the readers co-operate in order to conduct tag identification in a private and scalable way; (ii) a communication protocol for the proposed architecture is defined and assessed. The proposed architecture and protocol solve the scalability shortcomings of private RFID identification pointed out by Juels and Weis.

Agusti Solanas, Josep Domingo-Ferrer, Antoni Martínez-Ballesté

Proceedings of the 1st international workshop on privacy in location-based applications (PILBA), 12-23

Description: Location-Based Services (LBS) are gaining importance due to the advances in mobile networks and positioning technologies. Nevertheless, the wide deployment of LBS can jeopardise the privacy of their users, so ensuring user privacy is paramount to the success of those services. This article surveys the most relevant techniques for guaranteeing location privacy to LBS users. The rigid dichotomy between schemes which rely on Trusted Third Parties (TTP-based) and those which do not (TTP-free) is emphasised. Also, the convenience of both approaches is discussed and some ideas on the future of location privacy in these services are sketched.

David Rebollo-Monedero, Jordi Forné, Agusti Solanas, Antoni Martínez-Ballesté

Computer Communications 33 (6), 762-774

Description: Privacy and security are paramount in 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 does not assume that users or providers can be completely trusted with regard to privacy, and does not rely 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. Our protocol is analyzed in terms of privacy, network traffic, and processing overhead. We define the concept of guaranteed privacy breach probability, and we show that our proposal provides exponential scalability in that probability, at the expense of a linear relative network cost.

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