Measurement of Neutrino-Nucleon Neutral Current Elastic Scattering in MiniBooNE

Using a high-statistics sample of neutral current elastic neutrino interactions, MiniBooNE measured the flux-averaged neutral current elastic differential cross-section on mineral oil ($CH_2$). Using the latter, a $\chi^2$ test of MC with different values of the axial vector mass has been performed. Also, a possibility of using a sample of neutral current elastic proton-enriched events above Cherenkov threshold to measure the ratio $\nu p\to \nu p /\nu N\to \nu N$ is discussed. This ratio is sensitive to the strange quark contribution to the nucleon spin, $\Delta s$.Comment: 6 pages, 4 figures, 2 tables, Proceedings of the 6th International Workshop on Neutrino-Nucleus Interactions in the Few-GeV Region (NuInt09

A Survey on Industrial Control System Testbeds and Datasets for Security Research

The increasing digitization and interconnection of legacy Industrial Control Systems (ICSs) open new vulnerability surfaces, exposing such systems to malicious attackers. Furthermore, since ICSs are often employed in critical infrastructures (e.g., nuclear plants) and manufacturing companies (e.g., chemical industries), attacks can lead to devastating physical damages. In dealing with this security requirement, the research community focuses on developing new security mechanisms such as Intrusion Detection Systems (IDSs), facilitated by leveraging modern machine learning techniques. However, these algorithms require a testing platform and a considerable amount of data to be trained and tested accurately. To satisfy this prerequisite, Academia, Industry, and Government are increasingly proposing testbed (i.e., scaled-down versions of ICSs or simulations) to test the performances of the IDSs. Furthermore, to enable researchers to cross-validate security systems (e.g., security-by-design concepts or anomaly detectors), several datasets have been collected from testbeds and shared with the community. In this paper, we provide a deep and comprehensive overview of ICSs, presenting the architecture design, the employed devices, and the security protocols implemented. We then collect, compare, and describe testbeds and datasets in the literature, highlighting key challenges and design guidelines to keep in mind in the design phases. Furthermore, we enrich our work by reporting the best performing IDS algorithms tested on every dataset to create a baseline in state of the art for this field. Finally, driven by knowledge accumulated during this survey's development, we report advice and good practices on the development, the choice, and the utilization of testbeds, datasets, and IDSs

Supporting metropolitan Venice coastline climate adaptation. A multi-vulnerability and exposure assessment approach

Urban planning for adaptation to climate change privileges the construction of cognitive frameworks developed through the use of new spatial technologies and open-source databases. The significant and most highly innovative aspect concerns how resilience to CC under conditions of vulnerability and risk is defined, monitored and assessed. Based on these premises, this paper aims to explore a new methodology of climate vulnerability, exposure and risk analysis through multicriteria assessment techniques by activating a case study in the coastal municipality of Jesolo (Italy). Taking into consideration three main weather-climate impacts (Urban Flooding, Coastal Flooding and Urban Heat Island) the methodology searches for the best geo-referenced data that can best describe the recognizing impact of the cumulative impact condition through testing a GIS-based multi-attribute exploratory procedure. Intersectoral and multilevel vulnerability conditions at different spatial scales are configured. The analysis methodology continues using open source data (from Open Street Map) to construct local exposure information layers. Exposure combined with spatial vulnerability conditions allows the generation of multi-hazard mapping. Experimentation with multi-hazard climate-oriented spatial assessment can guide planning and public decision-making in new policy domains and target mitigation and adaptation actions in land planning, management and regulation practices. Finally, the proposed methodology can activate stakeholder engagement processes within municipalities to discuss the actual perceived risk and begin a collaborative journey with citizens to identify best practices and solutions to adopt in the areas indicated by the risk mapping

Hyperloop: A Cybersecurity Perspective

Hyperloop is among the most prominent future transportation systems. First introduced by Elon Musk, Hyperloop concept involves novel technologies to allow traveling at a maximum speed of 1220km/h, while guaranteeing sustainability. Due to the system's performance requirements and the critical infrastructure it represents, its safety and security need to be carefully considered. In cyber-physical systems, cyberattacks could lead to safety issues with catastrophic consequences, both on the population and the surrounding environment. Therefore, the cybersecurity of all the components and links in Hyperloop represents a fundamental challenge. To this day, no research investigated the cyber security of the technology used for Hyperloop. In this paper, we propose the first analysis of the cybersecurity challenges raised by Hyperloop technology. We base our analysis on the related works on Hyperloop, distilling the common features which will be likely to be present in the system. Furthermore, we provide an analysis of possible directions on the Hyperloop infrastructure management, together with their security concerns. Finally, we discuss possible countermeasures and future directions for the security of the future Hyperloop design.Comment: 9 pages, 4 figures, 1 tabl

EVScout2.0: Electric Vehicle Profiling Through Charging Profile

EVs (Electric Vehicles) represent a green alternative to traditional fuel-powered vehicles. To enforce their widespread use, both the technical development and the security of users shall be guaranteed. Privacy of users represents one of the possible threats impairing EVs adoption. In particular, recent works showed the feasibility of identifying EVs based on the current exchanged during the charging phase. In fact, while the resource negotiation phase runs over secure communication protocols, the signal exchanged during the actual charging contains features peculiar to each EV. A suitable feature extractor can hence associate such features to each EV, in what is commonly known as profiling. In this paper, we propose EVScout2.0, an extended and improved version of our previously proposed framework to profile EVs based on their charging behavior. By exploiting the current and pilot signals exchanged during the charging phase, our scheme is able to extract features peculiar for each EV, allowing hence for their profiling. We implemented and tested EVScout2.0 over a set of real-world measurements considering over 7500 charging sessions from a total of 137 EVs. In particular, numerical results show the superiority of EVScout2.0 with respect to the previous version. EVScout2.0 can profile EVs, attaining a maximum of 0.88 recall and 0.88 precision. To the best of the authors' knowledge, these results set a new benchmark for upcoming privacy research for large datasets of EVs

Toward a trans-regional vulnerability assessment for Alps. A methodological approach to land cover changes over alpine landscapes, supporting urban adaptation

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Multi-Risk Climate Mapping for the Adaptation of the Venice Metropolitan Area

Climate change risk reduction requires cities to undertake urgent decisions. One of the principal obstacles that hinders effective decision making is insufficient spatial knowledge frameworks. Cities climate adaptation planning must become strategic to rethink and transform urban fabrics holistically. Contemporary urban planning should merge future threats with older and unsolved criticalities, like social inequities, urban conflicts and \u201cdrosscapes\u201d. Retrofitting planning processes and redefining urban objectives requires the development of innovative spatial information frameworks. This paper proposes a combination of approaches to overcome knowledge production limits and to support climate adaptation planning. The research was undertaken in collaboration with the Metropolitan City of Venice and the Municipality of Venice, and required the production of a multi-risk climate atlas to support their future spatial planning efforts. The developed tool is a Spatial Decision Support System (SDSS), which aids adaptation actions and the coordination of strategies. The model recognises and assesses two climate impacts: Urban Heat Island and Flooding, representing the Metropolitan City of Venice (CMVE) as a case study in complexity. The model is composed from multiple assessment methodologies and maps both vulnerability and risk. The atlas links the morphological and functional conditions of urban fabrics and land use that triggers climate impacts. The atlas takes the exposure assessment of urban assets into account, using this parameter to describe local economies and social services, and map the uneven distribution of impacts. The resulting tool is therefore a replicable and scalable mapping assessment able to mediate between metropolitan and local level planning systems

Assessment of high-frequency steady-state visual evoked potentials from below-the-hairline areas for a brain-computer interface based on Depth-of-Field

Background and Objective: Recently, a promising Brain-Computer Interface based on Steady-State Visual Evoked Potential (SSVEP-BCI) was proposed, which composed of two stimuli presented together in the center of the subject's field of view, but at different depth planes (Depth-of-Field setup). Thus, users were easily able to select one of them by shifting their eye focus. However, in that work, EEG signals were collected through electrodes placed on occipital and parietal regions (hair-covered areas), which demanded a long preparation time. Also, that work used low-frequency stimuli, which can produce visual fatigue and increase the risk of photosensitive epileptic seizures. In order to improve the practicality and visual comfort, this work proposes a BCI based on Depth-of-Field using the high-frequency SSVEP response measured from below-the-hairline areas (behind-the-ears). Methods: Two high-frequency stimuli (31 Hz and 32 Hz) were used in a Depth-of-Field setup to study the SSVEP response from behind-the-ears (TP9 and TP10). Multivariate Spectral F-test (MSFT) method was used to verify the elicited response. Afterwards, a BCI was proposed to command a mobile robot in a virtual reality environment. The commands were recognized through Temporally Local Multivariate Synchronization Index (TMSI) method. Results: The data analysis reveal that the focused stimuli elicit distinguishable SSVEP response when measured from hairless areas, in spite of the fact that the non-focused stimulus is also present in the field of view. Also, our BCI shows a satisfactory result, reaching average accuracy of 91.6% and Information Transfer Rate (ITR) of 5.3 bits/min. Conclusion: These findings contribute to the development of more safe and practical BCI.Fil: Floriano, Alan. Universidade Federal do Espírito Santo; BrasilFil: Delisle Rodriguez, Denis. Universidade Federal do Espírito Santo; BrasilFil: Diez, Pablo Federico. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Bastos Filho, Teodiano Freire. Universidade Federal do Espírito Santo; Brasi