1,720,978 research outputs found
Preserving context security in AWS IoT Core
No full textCloud computing platforms are widely used as enabling frameworks for the Internet of Things. Within this context, a number of peripheral devices are connected to the middleware and constantly communicate raw data in order for them to be processed. Although several countermeasures were designed (and often adopted) in order to secure the communication channel and to ensure device and back-end authentication, several deployed IoT solution are subject to context security threats, where authenticated devices act in an allowed yet unexpected way and trigger undesired processing tasks in the back-end. As AWS IoT Core is currently the most adopted middleware in this context, this paper proposes a practical solution to achieve context security in such a scenario
libSBF-cpp
No full textThe Spatial Bloom Filters (SBF) are a compact, set-based data structure that extends the original Bloom filter concept. An SBF represents and arbitrary number of sets, and their respective elements (as opposed to Bloom filters, which represent the elements of a single set). SBFs are particularly suited to be used in privacy-preserving protocols, as set-membership queries (i.e. the process of verifying if an element is in a set) can be easily computed over an encrypted SBF, through (somewhat) homomorphic encryption. Spatial Bloom Filters have been first proposed for use in location-privacy application, but have found application in a number of domains, including network security and the Internet of Things. The libSBF-cpp repository contains the C++ implementation of the SBF data structure. The SBF class is provided, as well as various methods for managing the filter
Journal of Surveillance, Security and Safety
No full textJournal of Surveillance, Security and Safety (JSSS) is an international, peer-reviewed, open access journal which provides a forum for the publication of papers addressing the variety of theoretical, methodological, epistemological, empirical and practical issues concerns reflected in the field of information security, cyber security, machine learning, emerging technologies, and their applications
IoT Manager Android client
No full textIoT Manager is a general framework which allows users to deal with heterogeneous sensor networks within the smart city context. It is composed by a client component (front-end) which delivers useful information gathered by sensors (depending on the user's position and settings) and by a server component (back-end) which collects data from sensor networks and exposes them to the front-end. The framework natively manages georeferencing from both the user's and the sensors' perspective
Privacy and Security for Location-based Services and Devices
No full textJournal of Information Security and Applications (JISA) focuses on the original research and practice-driven applications with relevance to information security and applications. JISA provides a common linkage between a vibrant scientific and research community and industry professionals by offering a clear view on modern problems and challenges in information security, as well as identifying promising scientific and "best-practice" solutions. JISA issues offer a balance between original research work and innovative industrial approaches by internationally renowned information security experts and researchers
IoT Manager: an open-source IoT framework for smart cities
Full text linkRecent 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
IoT Manager: a Case Study of the Design and Implementation of an Open Source IoT Platform
No full textIoT represents one of the most insightful trends concerning ICT. As we assist to a growing diffusion of heterogeneous sensor networks deployed all over urban areas, one of the main concerns is to provide the community with versatile and easy-to-go frameworks capable to serve and to organize data collected by these sensors. However, as we may notice, the world largest
information technology companies tend to release user friendly IoT platforms and services avoiding to reveal the know-how
concerning design and implementation details of these products. As a consequence of this business strategy, a common trend
for universities and other teaching institutions is to use these mainstream IoT platforms during their classes in a ’as a service’ fashion, omitting to unveil technical details and design strategies these platforms rely on. In this paper, we present IoT Manager, a general framework designed for sensor networks management which was completely designed and implemented within the University of Bologna. Our main aim is to provide the scientific community with a detailed implementation strategy concerning a specific IoT platform in order to disseminate such topics in a more precise and understandable way, both for research and teaching purposes
A Heuristic for Direct Product Graph Decomposition
Full text linkIn this paper we describe a heuristic for decomposing a directed graph
into factors according to the direct product (also known as Kronecker, cardinal or tensor
product). Given a directed, unweighted graph G with adjacency matrix Adj(G), our
heuristic aims at identifying two graphs G 1 and G 2 such that G = G 1 × G 2 , where
G 1 × G 2 is the direct product of G 1 and G 2 . For undirected, connected graphs it has
been shown that graph decomposition is “at least as difficult” as graph isomorphism;
therefore, polynomial-time algorithms for decomposing a general directed graph into
factors are unlikely to exist. Although graph factorization is a problem that has been
extensively investigated, the heuristic proposed in this paper represents – to the best
of our knowledge – the first computational approach for general directed, unweighted
graphs. We have implemented our algorithm using the MATLAB environment; we
report on a set of experiments that show that the proposed heuristic solves reasonably-
sized instances in a few seconds on general-purpose hardware. Although the proposed
heuristic is not guaranteed to find a factorization, even if one exists; however, it always
succeeds on all the randomly-generated instances used in the experimental evaluation
Spatial bloom filter in named data networking: a memory efficient solution
No full textAmong the possible future Internet architectures, Information Centric Networking (ICN) is the most promising one and researchers working on the Named Data Networking (NDN) project are putting efforts towards its deployment in a real scenario. To properly handle content names, the different components of an NDN network need efficient and scalable data structures. In this paper, we propose a new data structure to support the NDN forwarding procedure by replacing the current Forwarding Information Base (FIB): the Spatial Bloom Filter (SBF), a probabilistic data structure that guarantees fast lookup and efficient memory consumption. Through a set of simulations run to compare the performance of FIB and SBF, we found that the latter uses less than 5 KB of data to handle 106 queried interests, with a (negligible) probability 10-4 of false positive events. Conversely, the FIB requires up to 2.5 GB of data in disadvantageous cases, e.g. when interests are composed of a considerable number of components
Probabilistic properties of the spatial bloom filters and their relevance to cryptographic protocols
Full text linkThe 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
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