Pericle Perazzo

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Location-based services rise high privacy concerns because they make it possible to collect and infer sensitive information from a per-son's positions and mobility traces. Many solutions have been proposed to safeguard the users' privacy, at least to a certain extent. However, they generally lack of a convincing experimental validation with real human(More)
—Distance-bounding protocols are able to measure a secure upper bound to the distance between two devices. They are designed to resist to reduction attacks, whose objective is reducing the measured distance. In this paper we focus on the opposite problem, the enlargement attack, which is aimed at enlarging the measured distance. We analyze the feasibility(More)
In this paper, we study the sensor localization problem using a drone. Our goal is to localize each sensor in the deployment area ensuring a predefined localization precision, i.e., a bound on the position error, whatever is the drone's altitude. We show how to guarantee a-priori the precision localization by satisfying few conditions. Such conditions are(More)
As location-based services emerge, many people feel exposed to high privacy threats. Privacy protection is a major challenge for such services and related applications. A simple approach is perturbation, which adds an artificial noise to positions and returns an obfuscated measurement to the requester. Our main finding is that, unless the noise is chosen(More)
The success of location-based services is growing together with the diffusion of GPS-equipped smart devices. As a consequence, privacy concerns are raising year by year. Location privacy is becoming a major interest in research and industry world, and many solutions have been proposed for it. One of the simplest and most flexible approaches is obfuscation,(More)
—In the next few years, we will see the upcom-ing of location-based services. Such LBSs will be extremely heterogeneous. Protecting the privacy of the users in such a situation requires flexible approaches. A single privacy protection mechanism is often insufficient. The contribution of this paper is twofold. First we present LbSprint, a middleware(More)
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