38 research outputs found
An anonymous inter-network routing protocol for the Internet of Things
With the diffusion of the Internet of Things (IoT), computing is becoming increasingly pervasive, and different heterogeneous networks are integrated into larger systems. However, as different networks managed by different parties and with different security requirements are interconnected, security becomes a primary concern. IoT nodes, in particular, are often deployed “in the open”, where an attacker can gain physical access to the device. As nodes can be deployed in unsurveilled or even hostile settings, it is crucial to avoid escalation from successful attacks on a single node to the whole network, and from there to other connected networks. It is therefore necessary to secure the communication within IoT networks, and in particular, maintain context information private, including the network topology and the location and identity of the nodes. In this paper, we propose a protocol achieving anonymous routing between different interconnected networks, designed for the Internet of Things and based on the spatial Bloom filter (SBF) data structure. The protocol enables private communication between the nodes through the use of anonymous identifiers, which hide their location and identity within the network. As routing information is encrypted using a homomorphic encryption scheme, and computed only in the encrypted domain, the proposed routing strategy preserves context privacy, preventing adversaries from learning the network structure and topology. This, in turn, significantly reduces their ability to gain valuable network information from a successful attacks on a single node of the network, and reduces the potential for attack escalation
Bloom filter variants for multiple sets: a comparative assessment
In this paper we compare two probabilistic data structures for association
queries derived from the well-known Bloom filter: the shifting Bloom filter
(ShBF), and the spatial Bloom filter (SBF). With respect to the original data
structure, both variants add the ability to store multiple subsets in the same
filter, using different strategies. We analyse the performance of the two data
structures with respect to false positive probability, and the inter-set error
probability (the probability for an element in the set of being recognised as
belonging to the wrong subset). As part of our analysis, we extended the
functionality of the shifting Bloom filter, optimising the filter for any
non-trivial number of subsets. We propose a new generalised ShBF definition
with applications outside of our specific domain, and present new probability
formulas. Results of the comparison show that the ShBF provides better space
efficiency, but at a significantly higher computational cost than the SBF
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
Where have the children with epilepsy gone? An observational study of seizure-related accesses to emergency department at the time of COVID-19
Purpose: The COVID-19 pandemic and related lockdown measures drastically changed health care and emergency services utilization. This study evaluated trends in emergency department (ED) access for seizure-related reasons in the first 8 weeks of lockdown in Italy.
Methods: All ED accesses of children (<14 years of age) at two university hospitals, in Turin and Rome, Italy, between January 6, 2020 and April 21, 2020, were examined and compared with the corresponding periods of 2019.
Results: During the COVID-19 lockdown period (February 23-April 21, 2020), there was a 72 % decrease in all pediatric ED accesses over the corresponding 2019 period (n = 3,395 vs n = 12,128), with a 38 % decrease in seizure-related accesses (n = 41 vs n = 66). The observed decrease of seizure-related ED accesses was not accompanied by significant changes in age, sex, type of seizure, or hospitalization rate after the ED visit.
Conclusion: The COVID-19 lockdown was accompanied by a sudden decrease in seizure-related hospital emergency visits. School closure, social distancing, reduced risk of infection, and increased parental supervision are some of the factors that might have contributed to the findin
Alexithymia, Metacognition, and Theory of Mind in Children and Preadolescents With Migraine Without Aura (MWoA): A Case-Control Study
Background: Some studies have demonstrated the high impact of headache and migraine in several areas of children and adolescents’ life. In recent years, there has been an increase in scientific interest in the relationship between migraine and emotional regulation, investigating the possible consequences of emotional dysregulation on physical and mental health. While some studies have been carried out on the relationship between alexithymia and headache or migraine (especially in adults), no data exist on relationship between Theory of Mind (TOM), metacognition, and alexithymia in children and adolescents with migraine. Methods: Children with diagnosis of migraine without aura (MWoA) (36 males and 34 females) were compared to a healthy control group (31 males and 39 females). The age range was from 8 to 13 years in both groups. All children completed the Alexithymia Questionnaire for Children (AQC) for the assessment of alexithymia levels and the Domain of Social Perception included in the NEPSY-II to evaluate levels of TOM. Metacognitive development was evaluated with Io e La Mia Mente for children aged between 8 and 10 years and with Metacognitions Questionnaire for Children (MCQ-C) for children from 11 to 13. Results: There were no differences between children with MWoA and the control group in metacognitive abilities; only in the subscale “Negative Meta Worrying” of MCQ-C girls scored higher than boys, regardless of the group they were part of. Also, in the NEPSY-II subscale there were no statistically significant differences between the two groups. Children with MWoA scored higher in the AQC subscales “Difficulty Identifying Feelings” and “Difficulty Describing Feelings” than controls. Moreover, children between 8 and 10 years statistically differed from older children in “Difficulty Identifying Feelings” and in Total Score. Conclusion: Our data suggest that children with MWoA have no metacognitive and TOM problems compared to a healthy group. The experimental group showed higher traits of alexithymia, confirming what suggested by other studies in the literature. Future research will have to focus on migraine with aura and tension-type headache to evaluate any differences with children with MWoA
Location privacy without mutual trust: The spatial Bloom filter
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 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. 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
ARIANNA: A research environment for neuroimaging studies in autism spectrum disorders
The complexity and heterogeneity of Autism Spectrum Disorders (ASD) require the implementation of dedicated analysis techniques to obtain the maximum from the interrelationship among many variables that describe affected individuals, spanning from clinical phenotypic characterization and genetic profile to structural and functional brain images. The ARIANNA project has developed a collaborative interdisciplinary research environment that is easily accessible to the community of researchers working on ASD (https://arianna.pi.infn.it). The main goals of the project are: to analyze neuroimaging data acquired in multiple sites with multivariate approaches based on machine learning; to detect structural and functional brain characteristics that allow the distinguishing of individuals with ASD from control subjects; to identify neuroimaging-based criteria to stratify the population with ASD to support the future development of personalized treatments. Secure data handling and storage are guaranteed within the project, as well as the access to fast grid/cloud-based computational resources. This paper outlines the web-based architecture, the computing infrastructure and the collaborative analysis workflows at the basis of the ARIANNA interdisciplinary working environment. It also demonstrates the full functionality of the research platform. The availability of this innovative working environment for analyzing clinical and neuroimaging information of individuals with ASD is expected to support researchers in disentangling complex data thus facilitating their interpretation
Cloning and Tampering Threats in e-Passports
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\u2019s 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\u2019s specifications (currently under discussion), a careless implementation of the inspection procedure may lead to unsuccessful detection of cloned e-Passports
A privacy-aware zero interaction smart mobility system
Smart cities often rely on technological innovations to improve citizens’ safety and quality of life. This paper presents a novel smart mobility system that facilitates people’s access to public mobility while preserving their privacy. In contrast to several well-known smart mobility systems discussed in this paper, the one we propose combines privacy guarantees with user friendliness. Specifically, the system is based on a zero-interaction approach whereby a person can use public transport services without any need to perform explicit actions. Operations related to ticket purchases and validation were fully automated. The system is also designed with the privacy-by-design paradigm to preserve user privacy as much as possible. Throughout the paper, several technical details are discussed as well to describe a prototype version of the system that was implemented. The prototype was successfully tested in the city of Imola (Emilia Romagna, Italy) to prove the validity of the system in the field
IoT Manager: an open-source IoT framework for smart cities
Recent surveys concerning Internet of Things confirm that there are 20 billion connected devices and counting all around the world. As we assist to the convergence of the IoT and the cloud computing paradigms, sensor networks are being deployed everywhere and grow both in number and significance. One of the main concerns is thus to provide the community with versatile and resilient frameworks capable to store and rearrange data collected by these sensors. However, the world largest information technology companies tend to release products in a as a service fashion, avoiding to reveal the know-how concerning design and implementation details. As a consequence, a common trend for academic institutions is to use these mainstream IoT platforms as 'black boxes'. In this paper we discuss some of the most commonly adopted IoT platforms and we present IoT Manager, a general framework designed for sensor networks management which was entirely developed within the University of Bologna. Through this case study, we provide the scientific community with a detailed implementation strategy concerning our specific IoT solution. Our results are supported from a LGPL realese of the IoT Manager client in order to serve as a test bed both for research and teaching purposes