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As location-based services emerge, many people feel exposed to high privacy threats. Privacy protection is a major challenge for such applications. A broadly used 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 properly, these(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)
Many dependable systems rely implicitly on the integrity of the positions of their components. For example, let us consider a sensor network for pollution monitoring: it is sufficient that a hostile actor physically moves some sensors to completely disrupt the monitoring. In such scenarios, a key question is: how to securely verify the positions of devices?(More)
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 make it possible to determine a trusted upper bound on the distance between two devices. Their key property is to resist reduction attacks, i.e., attacks aimed at reducing the distance measured by the protocol. Recently, researchers have also focused on enlargement attacks, aimed at enlarging the measured distance. Providing(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)
In the next few years, we will see the upcoming 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 two-fold. First we present LbSprint, a middleware(More)
Wireless sensor networks enable a wealth of new applications in areas such as military, medical, environmental, transportation, smart city, and so on. In many of these scenarios, we need to measure in a secure way the positions of the sensors. Existing range-based techniques for secure positioning require a burdensome infrastructure, with many fixed(More)
Many dependable systems rely on the integrity of the position of their components. In such systems, two key problems are secure localization and secure location verification of the components. Researchers proposed several solutions, which generally require expensive infrastructures of several fixed stations (<italic>anchors</italic>) with trusted positions.(More)