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

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

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

Real-world assessment of healthcare provided by the National Health Service: The network of regional Beaver research platforms

Real-world evidence can provide answers on healthcare utilization and appropriateness, post-marketing drugs safety and comparative effectiveness, and cost-effectiveness profiles of healthcare pathways. Healthcare utilization databases, possibly integrated with drug and disease registries, electronic medical records, survey and cohort data (i.e. real-world data), allow to trace healthcare ‘footprints’ left from beneficiaries of National Health Service. Beaver is a research platform available on demand to Italian regions which we developed for computing indicators of healthcare utilization and clinical outcomes, as well as for generating evidence on effectiveness and cost-effectiveness profile. Two distinct solutions may be adopted. One, the so-called Beaver Light front-end allows to automatically compute health indicators of adherence to official guidelines. Two, the so-called Beaver Full front-end involves an eight-step procedure entirely driven by the study protocol. In order to fulfil the directives recently issued by the European Parliament and Council and the Italian Authority for the protection of individual data, the platform resides in each region’s infrastructure, so limiting the free movement of electronic health data. Indeed, regional authorities should be responsible for data safety and for allowing data accessibility. The use of standardized and validated algorithms enables to obtain regional estimates that, being obtained by employing regional platforms containing data extracted with standardized procedure, may be compared and possibly summarized by using common meta-analytic techniques. In conclusion, the Beaver regional platform is a promising tool which may contribute to stimulate healthcare research in Italy

SSR Locator: Tool for Simple Sequence Repeat Discovery Integrated with Primer Design and PCR Simulation

Microsatellites or SSRs (simple sequence repeats) are ubiquitous short tandem duplications occurring in eukaryotic organisms. These sequences are among the best marker technologies applied in plant genetics and breeding. The abundant genomic, BAC, and EST sequences available in databases allow the survey regarding presence and location of SSR loci. Additional information concerning primer sequences is also the target of plant geneticists and breeders. In this paper, we describe a utility that integrates SSR searches, frequency of occurrence of motifs and arrangements, primer design, and PCR simulation against other databases. This simulation allows the performance of global alignments and identity and homology searches between different amplified sequences, that is, amplicons. In order to validate the tool functions, SSR discovery searches were performed in a database containing 28 469 nonredundant rice cDNA sequences

The cAMP-HMGA1-RBP4 system: a novel biochemical pathway for modulating glucose homeostasis

<p>Abstract</p> <p>Background</p> <p>We previously showed that mice lacking the high mobility group A1 gene (<it>Hmga1</it>-knockout mice) developed a type 2-like diabetic phenotype, in which cell-surface insulin receptors were dramatically reduced (below 10% of those in the controls) in the major targets of insulin action, and glucose intolerance was associated with increased peripheral insulin sensitivity. This particular phenotype supports the existence of compensatory mechanisms of insulin resistance that promote glucose uptake and disposal in peripheral tissues by either insulin-dependent or insulin-independent mechanisms. We explored the role of these mechanisms in the regulation of glucose homeostasis by studying the <it>Hmga1</it>-knockout mouse model. Also, the hypothesis that increased insulin sensitivity in <it>Hmga1</it>-deficient mice could be related to the deficit of an insulin resistance factor is discussed.</p> <p>Results</p> <p>We first show that HMGA1 is needed for basal and cAMP-induced retinol-binding protein 4 (<it>RBP4</it>) gene and protein expression in living cells of both human and mouse origin. Then, by employing the <it>Hmga1</it>-knockout mouse model, we provide evidence for the identification of a novel biochemical pathway involving HMGA1 and the RBP4, whose activation by the cAMP-signaling pathway may play an essential role for maintaining glucose metabolism homeostasis <it>in vivo</it>, in certain adverse metabolic conditions in which insulin action is precluded. In comparative studies of normal and mutant mice, glucagon administration caused a considerable upregulation of HMGA1 and RBP4 expression both at the mRNA and protein level in wild-type animals. Conversely, in <it>Hmga1</it>-knockout mice, basal and glucagon-mediated expression of RBP4 was severely attenuated and correlated inversely with increased <it>Glut4 </it>mRNA and protein abundance in skeletal muscle and fat, in which the activation state of the protein kinase Akt, an important downstream mediator of the metabolic effects of insulin on Glut4 translocation and carbohydrate metabolism, was simultaneously increased.</p> <p>Conclusion</p> <p>These results indicate that HMGA1 is an important modulator of <it>RBP4 </it>gene expression <it>in vivo</it>. Further, they provide evidence for the identification of a novel biochemical pathway involving the cAMP-HMGA1-RBP4 system, whose activation may play a role in glucose homeostasis in both rodents and humans. Elucidating these mechanisms has importance for both fundamental biology and therapeutic implications.</p

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

MicroRNAs for the Diagnosis and Management of Malignant Pleural Mesothelioma: A Literature Review

Malignant pleural mesothelioma (MPM) is a rare and aggressive tumor with a variable incidence among different countries. Occupational asbestos exposure is the most important etiological factor and a very long latency period is widely reported. In the early phase of the disease, clinical signs are absent or not specific. For this reason, the diagnosis is frequently achieved only in the advanced stages. The histopathological diagnosis per se is also very complex, and no known factor can predict the prognosis with certainty. Nonetheless, current survival rates remain very low, despite the use of standard treatments, which include surgery, chemotherapy and radiotherapy. The identification of new prognostic and/or diagnostic biomarkers, and the discovery of therapeutic targets is a priority and could lead to a real significant impact on the management of malignant pleural mesothelioma. In this scenario, the role of microRNAs is becoming increasingly relevant, with the promise of a quick translation in the current clinical practice. Despite the relative novelty of this field, the number of works and candidate microRNAs that are present in literature is striking. Unfortunately, to date the microRNAs with the most clinical relevance for MPM are still matter of debate, probably due to the variety of approaches, techniques, and collected samples. Although specific microRNAs (e.g., let-7, miR-15 and miR-16, miR-21, miR-34a, and the miR-200 family) have been reported several times from different groups, the heterogeneity of published data reinforces the need of more comprehensive and unified studies on this topic. In this review we collect and discuss the studies focused on the involvement of microRNAs in different aspects of MPM, from their biological role in tumorigenesis and progression, to their possible application as diagnostic, prognostic and predictive biomarkers. Lastly, we examine their potential value as for the design of therapeutic approaches that could benefit MPM patients