Mind My Value: a decentralized infrastructure for fair and trusted IoT data trading

Internet of Things (IoT) data are increasingly viewed as a new form of massively distributed and large scale digital assets, which are continuously generated by millions of connected devices. The real value of such assets can only be realized by allowing IoT data trading to occur on a marketplace that rewards every single producer and consumer, at a very granular level. Crucially, we believe that such a marketplace should not be owned by anybody, and should instead fairly and transparently self-enforce a well defined set of governance rules. In this paper we address some of the technical challenges involved in realizing such a marketplace. We leverage emerging blockchain technologies to build a decentralized, trusted, transparent and open architecture for IoT traffic metering and contract compliance, on top of the largely adopted IoT brokered data infrastructure. We discuss an Ethereum-based prototype implementation and experimentally evaluate the overhead cost associated with Smart Contract transactions, concluding that a viable business model can indeed be associated with our technical approach

Query Interface for Smart City Internet of Things Data Marketplaces: A Case Study

Cities are increasingly getting augmented with sensors through public, private, and academic sector initiatives. Most of the time, these sensors are deployed with a primary purpose (objective) in mind (e.g., deploy sensors to understand noise pollution) by a sensor owner (i.e., the organization that invests in sensing hardware, for example, a city council). Over the last few years, communities undertaking smart city development projects have understood the importance of making the sensor data available to a wider community – beyond their primary usage. Different business models have been proposed to achieve this, including creating data marketplaces. The vision is to encourage new start-ups and small and medium-scale businesses to create novel products and services using sensor data to generate additional economic value. Currently, data are sold as pre-defined independent datasets (e.g., noise level and parking status data may be sold separately). This approach creates several challenges, such as (i) difficulties in pricing, which leads to higher prices (per dataset), (ii) higher network communication and bandwidth requirements, and (iii) information overload for data consumers (i.e., those who purchase data). We investigate the benefit of semantic representation and its reasoning capabilities towards creating a business model that offers data on-demand within smart city Internet of Things (IoT) data marketplaces. The objective is to help data consumers (i.e., small and medium enterprises (SMEs)) acquire the most relevant data they need. We demonstrate the utility of our approach by integrating it into a real-world IoT data marketplace (developed by synchronicity-iot.eu project). We discuss design decisions and their consequences (i.e., trade-offs) on the choice and selection of datasets. Subsequently, we present a series of data modeling principles and recommendations for implementing IoT data marketplaces

makeSense: Simplifying the Integration of Wireless Sensor Networks into Business Processes

A wide gap exists between the state of the art in developing Wireless Sensor Network (WSN) software and current practices concerning the design, execution, and maintenance of business processes. WSN software is most often developed based on low-level OS abstractions, whereas business process development leverages high-level languages and tools. This state of affairs places WSNs at the fringe of industry. The makeSense system addresses this problem by simplifying the integration of WSNs into business processes. Developers use BPMN models extended with WSN-specific constructs to specify the application behavior across both traditional business process execution environments and the WSN itself, which is to be equipped with application-specific software. We compile these models into a high-level intermediate language—also directly usable by WSN developers—and then into OS-specific deployment-ready binaries. Key to this process is the notion of meta-abstraction, which we define to capture fundamental patterns of interaction with and within the WSN. The concrete realization of meta-abstractions is application-specific; developers tailor the system configuration by selecting concrete abstractions out of the existing codebase or by providing their own. Our evaluation of makeSense shows that i) users perceive our approach as a significant advance over the state of the art, providing evidence of the increased developer productivity when using makeSense; ii) in large-scale simulations, our prototype exhibits an acceptable system overhead and good scaling properties, demonstrating the general applicability of makeSense; and, iii) our prototype—including the complete tool-chain and underlying system support—sustains a real-world deployment where estimates by domain specialists indicate the potential for drastic reductions in the total cost of ownership compared to wired and conventional WSN-based solutions

Protective Effects of Recombinant Human Angiogenin in Keratinocytes: New Insights on Oxidative Stress Response Mediated by RNases

Human angiogenin (ANG) is a 14-kDa ribonuclease involved in different pathophysiological processes including tumorigenesis, neuroprotection, inflammation, innate immunity, reproduction, the regeneration of damaged tissues and stress cell response, depending on its intracellular localization. Under physiological conditions, ANG moves to the cell nucleus where it enhances rRNA transcription; conversely, recent reports indicate that under stress conditions, ANG accumulates in the cytoplasmic compartment and modulates the production of tiRNAs, a novel class of small RNAs that contribute to the translational inhibition and recruitment of stress granules (SGs). To date, there is still limited and controversial experimental evidence relating to a hypothetical role of ANG in the epidermis, the outermost layer of human skin, which is continually exposed to external stressors. The present study collects compelling evidence that endogenous ANG is able to modify its subcellular localization on HaCaT cells, depending on different cellular stresses. Furthermore, the use of recombinant ANG allowed to determine as this special enzyme is effectively able to counter at various levels the alterations of cellular homeostasis in HaCaT cells, actually opening a new vision on the possible functions that this special enzyme can support also in the stress response of human skin

Human Cryptic Host Defence Peptide {GVF}27 Exhibits Anti-Infective Properties against Biofilm Forming Members of the Burkholderia cepacia Complex

Therapeutic solutions to counter Burkholderia cepacia complex (Bcc) bacteria are challenging due to their intrinsically high level of antibiotic resistance. Bcc organisms display a variety of potential virulence factors, have a distinct lipopolysaccharide naturally implicated in antimicrobial resistance. and are able to form biofilms, which may further protect them from both host defence peptides (HDPs) and antibiotics. Here, we report the promising anti-biofilm and immunomodulatory activities of human HDP GVF27 on two of the most clinically relevant Bcc members, Burkholderia multivorans and Burkholderia cenocepacia. The effects of synthetic and labelled GVF27 were tested on B. cenocepacia and B. multivorans biofilms, at three different stages of formation, by confocal laser scanning microscopy (CLSM). Assays on bacterial cultures and on human monocytes challenged with B. cenocepacia LPS were also performed. GVF27 exerts, at different stages of formation, antibiofilm effects towards both Bcc strains, a significant propensity to function in combination with ciprofloxacin, a relevant affinity for LPSs isolated from B. cenocepacia as well as a good propensity to mitigate the release of pro-inflammatory cytokines in human cells pre-treated with the same endotoxin. Overall, all these findings contribute to the elucidation of the main features that a good therapeutic agent directed against these extremely leathery biofilm-forming bacteria should possess

Safety and Efficacy of Subcutaneous Rituximab in Previously Untreated Patients with CD20+ Diffuse Large B-Cell Lymphoma or Follicular Lymphoma: Results from an Italian Phase IIIb Study

Subcutaneous (SC) rituximab may be beneficial in terms of convenience and tolerability, with potentially fewer and less severe administration-related reactions (ARRs) compared to the intravenous (IV) form. This report presents the results of a phase IIIb study conducted in Italy. The study included adult patients with CD20+ DLBCL or FL having received at least one full dose of IV RTX 375 mg/m2 during induction or maintenance. Patients on induction received ≥4 cycles of RTX SC 1400 mg plus standard chemotherapy and FL patients on maintenance received ≥6 cycles of RTX SC. Overall, 159 patients (73 DLBCL, 86 FL) were enrolled: 103 (54 DLBCL, 49 FL) completed induction and 42 patients with FL completed 12 maintenance cycles. ARRs were reported in 10 patients (6.3%), 3 (4.2%) with DLBCL and 7 (8.1%) with FL, all of mild severity, and resolved without dose delay/discontinuation. Treatment-emergent adverse events (TEAEs) and serious adverse events occurred in 41 (25.9%) and 14 patients (8.9%), respectively. Two patients with DLBCL had fatal events: Klebsiella infection (related to rituximab) and septic shock (related to chemotherapy). Neutropenia (14 patients, 8.9%) was the most common treatment-related TEAE. Two patients with DLBCL (2.8%) and 6 with FL (7.0%) discontinued rituximab due to TEAEs. 65.2% and 69.7% of patients with DLBCL and 67.9% and 73.6% of patients with FL had complete response (CR) and CR unconfirmed, respectively. The median time to events (EFS, PFS, and OS) was not estimable due to the low rate of events. At a median follow-up of 29.5 and 47.8 months in patients with DLBCL and FL, respectively, EFS, PFS, and OS were 70.8%, 70.8%, and 80.6% in patients with DLBCL and 77.9%, 77.9%, and 95.3% in patients with FL, respectively. The switch from IV to SC rituximab in patients with DLBCL and FL was associated with low risk of ARRs and satisfactory response in both groups. This trial was registered with NCT01987505

THREAT ANALYSIS AND DETECTION IN CRITICAL INFRASTRUCTURE SECURITY

Critical Infrastructure Protection against threats has become a major issue in modern society, due in particular to the traumatic terrorist attacks of New York and Washington (2001), Madrid (2004), London (2005) and to the very recently train bomb attack on the Nevsky Express from Moscow to St. Petersburg (November 2009). Such events highlighted the vulnerabilities of actual civil infrastructures and demonstrated that traditional concepts of Homeland Security did not match the current requirements. Critical infrastructures include physical assets as well as Information and Communication Technology services, networks and installations that constitute vital points of a country. Their protection has become an important and tricky activity which requires the development of innovative and multidisciplinary approaches in order to identify and mitigate vulnerabilities and risks, provide security operators with an acceptable situation awareness level in order to prevent threats, and coordinate emergency procedures after a natural catastrophe or a malicious attack. In this thesis we propose a protection strategy for critical infrastructures, made up of three main contributions. First of all, we present a quantitative methodology for risk management implemented in a specified tool, which allows for a cost/benefit analysis and also provides a valid support for the classification of threats; secondly, we propose an integration platform for sensor systems aims to solve heterogeneity issues of sensing technologies employed in modern security systems; finally we introduce a deterministic model-based detection engine aims to early detect threats against critical infrastructures by correlating events signaled by different sensor systems. Some experimental testbeds of the proposed solutions show how our protection strategy can be very effective in enhancing the security level of a critical rail-based infrastructure

A Secure Architecture for Re-Taskable Sensing Systems

Sensor Networks are considered a high-innovation potential branch in the field of network computing and are widely used in several application domains thanks to their cost effectiveness, flexibility and ease of deployment. They are well suited to a multitude of monitoring and surveillance applications and are often involved in mission-critical tasks, thus making security a primary concern. Many architectures and protocols have been proposed to address this issue, mainly based on cryptographic operations, but it still represents an open research area: in fact, in order to be effective, such techniques often require complex computations and a large amount of dedicated resources, which are not available on sensor platforms according to the existing technology. Nevertheless, if considering tiered sensor networks, where tiny motes coexist with more powerful nodes, it is possible to perform some complex and efficient security schemes by exploiting the different capabilities of nodes. In this paper we present a secure architectural proposal based on the Tenet system, a tiered re-taskable sensor network architecture. Specifically, we have integrated security features into the Tenet architecture in order to implement a hybrid cryptosystem. Such a cryptosystem combines symmetric and asymmetric cryptographic schemes to benefit of the security provided by asymmetric protocols and the better performance of symmetric ones