Luca Calderoni

Indoor localization in a hospital environment using Random Forest classifiers

A system able to localize patients in a hospital environment is proposed.The system relies on RFID technology and a combination of Random Forest classifiers.The system has been deployed in the emergency unit of a large Italian hospital.Accuracy, precision, complexity, robustness and scalability have been evaluated.Patients localization is correctly performed in 98% of cases. This paper proposes a new indoor localization system, based on RFID technology and a hierarchical structure of classifiers. This system has been specifically designed to work in unfriendly scenarios, where transmissions could be disturbed by other electronic devices or shielded walls. The infrastructure has been deployed and evaluated in the emergency unit of a large Italian hospital (48 rooms covering about 4000 m 2 ) to detect the room where lost or forgotten patients lie. Extensive experiments show the potential of such technology for indoor localization applications in terms of accuracy, precision, complexity, robustness and scalability. In 98% of cases the system localizes the correct room (83%) or one of its adjacency (15%).

Location-aware mobile services for a smart city: design, implementation and deployment

A smart city is a high-performance urban context, where citizens are more aware of, and more integrated into the city life, thanks to an intelligent city information system. In this paper we design, implement and deploy a smart application that retrieves and conveys to the user relevant information on the users surroundings. This case study application let us discuss the challenges involved in creating a location-aware mobile service based on live information coming from the city IT infrastructure. The service, that is currently being deployed in the Italian city of Cesena, has been designed with the goal of being a general model for future applications. In particular, we discuss location-aware and mobile development, cloud and cluster based geographical data storage, and spatial data computation. For each of these topics we provide implementation and deployment solutions based on currently available technology. In particular we propose an architecture based on a complex On-Line Transaction Processing (OLTP) infrastructure. Furthermore, this paper represents the first comprehensive, scientific study on the subject.

Deploying a network of smart cameras for traffic monitoring on a city kernel

A relevant aspect when evaluating the city smartness is related to the innovative approach to urban traffic management. We present a system called city kernel, designed to handle several subsystems, each addressing a specific sensor network and we describe an infrastructure for wide traffic control via a vision sensor network. This infrastructure consists of a network of smart cameras operating over an outdoor public lighting thanks to power line communication technology and equipped with a vehicle counting and classification algorithm. We discuss the deployment of this network on the city kernel and some related services exposed to urban actors.

Location privacy without mutual trust

We define a new data structure for location privacy based on bloom filters.We provide two privacy preserving protocols for location-aware services.We prove the security of the protocols and we analyze their efficiency.We provide a thorough evaluation of the data structure and we simulate the protocols. Location-aware applications are one of the biggest innovations brought by the smartphone era, and are effectively changing our everyday lives. But we are only starting to grasp the privacy risks associated with constant tracking of our whereabouts. In order to continue using location-based services in the future without compromising our privacy and security, we need new, privacy-friendly applications and protocols. In this paper, we propose a new compact data structure based on Bloom filters, designed to store location information. The spatial Bloom filter (SBF), as we call it, is designed with privacy in mind, and we prove it by presenting two private positioning protocols based on the new primitive. The protocols keep the users exact position private, but allow the provider of the service to learn when the user is close to specific points of interest, or inside predefined areas. At the same time, the points and areas of interest remain oblivious to the user. The two proposed protocols are aimed at different scenarios: a two-party setting, in which communication happens directly between the user and the service provider, and a three-party setting, in which the service provider outsources to a third party the communication with the user. A detailed evaluation of the efficiency and security of our solution shows that privacy can be achieved with minimal computational and communication overhead. The potential of spatial Bloom filters in terms of generality, security and compactness makes them ready for deployment, and may open the way for privacy preserving location-aware applications.

Spatial Bloom Filters: Enabling Privacy in Location-Aware Applications

The wide availability of inexpensive positioning systems made it possible to embed them into smartphones and other personal devices. This marked the beginning of location-aware applications, where users request personalized services based on their geographic position. The location of a user is, however, highly sensitive information: the user’s privacy can be preserved if only the minimum amount of information needed to provide the service is disclosed at any time. While some applications, such as navigation systems, are based on the users’ movements and therefore require constant tracking, others only require knowledge of the user’s position in relation to a set of points or areas of interest. In this paper we focus on the latter kind of services, where location information is essentially used to determine membership in one or more geographic sets. We address this problem using Bloom Filters (BF), a compact data structure for representing sets. In particular, we present an extension of the original Bloom filter idea: the Spatial Bloom Filter (SBF). SBF’s are designed to manage spatial and geographical information in a space efficient way, and are well-suited for enabling privacy in location-aware applications. We show this by providing two multi-party protocols for privacy-preserving computation of location information, based on the known homomorphic properties of public key encryption schemes. The protocols keep the user’s exact position private, but allow the provider of the service to learn when the user is close to specific points of interest, or inside predefined areas. At the same time, the points and areas of interest remain oblivious to the user.

Cloning and tampering threats in e-Passports

Abstract e-Passports present different security measures designed to safeguard their authenticity and more specifically to protect them from tampering and cloning attempts. Security protocols defined by International Civil Aviation Organization for this purpose (Passive Authentication, Active Authentication) should be enough to prevent such attacks. However, according to current specifications that regulate the Logical Data Structure of the e-Passport’s chip, it is feasible to bypass these protocols exploiting some flaws in the Inspection System. In this paper we show that as long as new documents will not be issued in compliance with new logical data structure’s specifications (currently under discussion), a careless implementation of the inspection procedure may lead to unsuccessful detection of cloned e-Passports.

Feather forking as a positive force: incentivising green energy production in a blockchain-based smart grid

Climate change represents a serious threat to the health of our planet and imposed a discussion upon energy waste and production. In this paper we propose a smart grid architecture relying on blockchain technology aimed at discouraging the production and distribution of non-renewable energy as the one derived from fossil fuel. Our model relies on a reverse application of a recently introduced attack to the blockchain based on chain forking. Our system involves both a central authority and a number of distributed peers representing the stakeholders of the energy grid. This system preserves those advantages derived from the blockchain and it also address some limitations such as energy waste for mining operations. In addition, the reverse attack we rely on allows to mitigate the behavior of a classic blockchain, which is intrinsecally self-regulated, and to trigger a sort of ethical action which penalizes non-renewable energy producers. Blacklisted stakeholders will be induced to provide their transaction with higher fees in order to preserve the selling rate.

Probabilistic properties of the spatial bloom filters and their relevance to cryptographic protocols

The classical Bloom filter data structure is a crucial component of hundreds of cryptographic protocols. It has been used in privacy preservation and secure computation settings, often in conjunction with the (somewhat) homomorphic properties of ciphers such as Paillier’s. In 2014, a new data structure extending and surpassing the capabilities of the classical Bloom filter has been proposed. The new primitive, called spatial Bloom filter (SBF) retains the hash-based membership-query design of the Bloom filter, but applies it to elements from multiple sets. Since its introduction, the SBF has been used in the design of cryptographic protocols for a number of domains, including location privacy and network security. However, due to the complex nature of this probabilistic data structure, its properties had not been fully understood. In this paper, we address this gap in knowledge and we fully explore the probabilistic properties of the SBF. In doing so, we define a number of metrics (such as emersion and safeness) useful in determining the parameters needed to achieve certain characteristics in a filter, including the false positive probability and inter-set error rate. This will in turn enable the design of more efficient cryptographic protocols based on the SBF, opening the way to their practical application in a number of security and privacy settings.