Segurança e privacidade em terminologia de rede

Security and Privacy are now at the forefront of modern concerns, and drive a significant part of the debate on digital society. One particular aspect that holds significant bearing in these two topics is the naming of resources in the network, because it directly impacts how networks work, but also affects how security mechanisms are implemented and what are the privacy implications of metadata disclosure. This issue is further exacerbated by interoperability mechanisms that imply this information is increasingly available regardless of the intended scope. This work focuses on the implications of naming with regards to security and privacy in namespaces used in network protocols. In particular on the imple- mentation of solutions that provide additional security through naming policies or increase privacy. To achieve this, different techniques are used to either embed security information in existing namespaces or to minimise privacy ex- posure. The former allows bootstraping secure transport protocols on top of insecure discovery protocols, while the later introduces privacy policies as part of name assignment and resolution. The main vehicle for implementation of these solutions are general purpose protocols and services, however there is a strong parallel with ongoing re- search topics that leverage name resolution systems for interoperability such as the Internet of Things (IoT) and Information Centric Networks (ICN), where these approaches are also applicable.Segurança e Privacidade são dois topicos que marcam a agenda na discus- são sobre a sociedade digital. Um aspecto particularmente subtil nesta dis- cussão é a forma como atribuímos nomes a recursos na rede, uma escolha com consequências práticas no funcionamento dos diferentes protocols de rede, na forma como se implementam diferentes mecanismos de segurança e na privacidade das várias partes envolvidas. Este problema torna-se ainda mais significativo quando se considera que, para promover a interoperabili- dade entre diferentes redes, mecanismos autónomos tornam esta informação acessível em contextos que vão para lá do que era pretendido. Esta tese foca-se nas consequências de diferentes políticas de atribuição de nomes no contexto de diferentes protocols de rede, para efeitos de segurança e privacidade. Com base no estudo deste problema, são propostas soluções que, através de diferentes políticas de atribuição de nomes, permitem introdu- zir mecanismos de segurança adicionais ou mitigar problemas de privacidade em diferentes protocolos. Isto resulta na implementação de mecanismos de segurança sobre protocolos de descoberta inseguros, assim como na intro- dução de mecanismos de atribuiçao e resolução de nomes que se focam na protecçao da privacidade. O principal veículo para a implementação destas soluções é através de ser- viços e protocolos de rede de uso geral. No entanto, a aplicabilidade destas soluções extende-se também a outros tópicos de investigação que recorrem a mecanismos de resolução de nomes para implementar soluções de intero- perabilidade, nomedamente a Internet das Coisas (IoT) e redes centradas na informação (ICN).Programa Doutoral em Informátic

Privacy and identity selection

Mestrado em Engenharia de Computadores e TelemáticaEste trabalho aborda algumas das tecnologias emergentes, que visam providenciar modelos com suporte para identidade, sobre a arquitectura da internet. Enquanto que tais propostas providenciam de facto modelos de identidade mais adequados para a Web 2.0, ignoram que a arquitectura sobre a qual assentam hão pode suportar os requisitos de privacidade necessários. A fim de demonstrar que é necessário providenciar garantias de privacidade nas camadas inferiores da arquitectura existentes, este trabalho apresenta uma implementação de demonstrac¸ ˜ao que explora vulnerabilidades da arquitectura existente a ataques de privacidade, assim como uma implementação que dá garantias de privacidade para múltiplas identidades. ABSTRACT: This work presents some of the technologies, that aim at introducing user centric identity models over the existing Internet architecture. While such technologies do provide suitable identity models for theWeb 2.0, they neglect that the underlying Internet architecture does not support the necessary privacy requirements for such models. As a demonstration that the underlying network layers must provide some privacy guarantees, this work presents an implementation that explores privacy vulnerabilities and proceeds to propose mechanisms that ensure privacy between multiple identities

Thrombus aspiration in patients with ST-elevation myocardial infarction: results of a national registry of interventional cardiology

BACKGROUND: We aimed to evaluate the impact of thrombus aspiration (TA) during primary percutaneous coronary intervention (P-PCI) in 'real-world' settings. METHODS: We performed a retrospective study, using data from the National Registry of Interventional Cardiology (RNCI 2006-2012, Portugal) with ST-elevation myocardial infarction (STEMI) patients treated with P-PCI. The primary outcome, in-hospital mortality, was analysed through adjusted odds ratio (aOR) and 95% confidence intervals (95%CI). RESULTS: We assessed data for 9458 STEMI patients that undergone P-PCI (35% treated with TA). The risk of in-hospital mortality with TA (aOR 0.93, 95%CI:0.54-1.60) was not significantly decreased. After matching patients through the propensity score, TA reduced significantly the risk of in-hospital mortality (OR 0.58, 95%CI:0.35-0.98; 3500 patients). CONCLUSIONS: The whole cohort data does not support the routine use of TA in P-PCI, but the results of the propensity-score matched cohort suggests that the use of selective TA may improve the short-term risks of STEMI..info:eu-repo/semantics/publishedVersio

Spectroscopic camera analysis of the roles of molecularly assisted reaction chains during detachment in JET L-mode plasmas

The roles of the molecularly assisted ionization (MAI), recombination (MAR) and dissociation (MAD) reaction chains with respect to the purely atomic ionization and recombination processes were studied experimentally during detachment in low-confinement mode (L-mode) plasmas in JET with the help of experimentally inferred divertor plasma and neutral conditions, extracted previously from filtered camera observations of deuterium Balmer emission, and the reaction coefficients provided by the ADAS, AMJUEL and H2VIBR atomic and molecular databases. The direct contribution of MAI and MAR in the outer divertor particle balance was found to be inferior to the electron-atom ionization (EAI) and electron-ion recombination (EIR). Near the outer strike point, a strong atom source due to the D+2-driven MAD was, however, observed to correlate with the onset of detachment at outer strike point temperatures of Te,osp = 0.9-2.0 eV via increased plasma-neutral interactions before the increasing dominance of EIR at Te,osp < 0.9 eV, followed by increasing degree of detachment. The analysis was supported by predictions from EDGE2D-EIRENE simulations which were in qualitative agreement with the experimental observations

Shattered pellet injection experiments at JET in support of the ITER disruption mitigation system design

A series of experiments have been executed at JET to assess the efficacy of the newly installed shattered pellet injection (SPI) system in mitigating the effects of disruptions. Issues, important for the ITER disruption mitigation system, such as thermal load mitigation, avoidance of runaway electron (RE) formation, radiation asymmetries during thermal quench mitigation, electromagnetic load control and RE energy dissipation have been addressed over a large parameter range. The efficiency of the mitigation has been examined for the various SPI injection strategies. The paper summarises the results from these JET SPI experiments and discusses their implications for the ITER disruption mitigation scheme

Disruption prediction at JET through deep convolutional neural networks using spatiotemporal information from plasma profiles

In view of the future high power nuclear fusion experiments, the early identification of disruptions is a mandatory requirement, and presently the main goal is moving from the disruption mitigation to disruption avoidance and control. In this work, a deep-convolutional neural network (CNN) is proposed to provide early detection of disruptive events at JET. The CNN ability to learn relevant features, avoiding hand-engineered feature extraction, has been exploited to extract the spatiotemporal information from 1D plasma profiles. The model is trained with regularly terminated discharges and automatically selected disruptive phase of disruptions, coming from the recent ITER-like-wall experiments. The prediction performance is evaluated using a set of discharges representative of different operating scenarios, and an in-depth analysis is made to evaluate the performance evolution with respect to the considered experimental conditions. Finally, as real-time triggers and termination schemes are being developed at JET, the proposed model has been tested on a set of recent experiments dedicated to plasma termination for disruption avoidance and mitigation. The CNN model demonstrates very high performance, and the exploitation of 1D plasma profiles as model input allows us to understand the underlying physical phenomena behind the predictor decision

Performance Comparison of Machine Learning Disruption Predictors at JET

Reliable disruption prediction (DP) and disruption mitigation systems are considered unavoidable during international thermonuclear experimental reactor (ITER) operations and in the view of the next fusion reactors such as the DEMOnstration Power Plant (DEMO) and China Fusion Engineering Test Reactor (CFETR). In the last two decades, a great number of DP systems have been developed using data-driven methods. The performance of the DP models has been improved over the years both for a more appropriate choice of diagnostics and input features and for the availability of increasingly powerful data-driven modelling techniques. However, a direct comparison among the proposals has not yet been conducted. Such a comparison is mandatory, at least for the same device, to learn lessons from all these efforts and finally choose the best set of diagnostic signals and the best modelling approach. A first effort towards this goal is made in this paper, where different DP models will be compared using the same performance indices and the same device. In particular, the performance of a conventional Multilayer Perceptron Neural Network (MLP-NN) model is compared with those of two more sophisticated models, based on Generative Topographic Mapping (GTM) and Convolutional Neural Networks (CNN), on the same real time diagnostic signals from several experiments at the JET tokamak. The most common performance indices have been used to compare the different DP models and the results are deeply discussed. The comparison confirms the soundness of all the investigated machine learning approaches and the chosen diagnostics, enables us to highlight the pros and cons of each model, and helps to consciously choose the approach that best matches with the plasma protection needs

New H-mode regimes with small ELMs and high thermal confinement in the Joint European Torus

New H-mode regimes with high confinement, low core impurity accumulation, and small edge-localized mode perturbations have been obtained in magnetically confined plasmas at the Joint European Torus tokamak. Such regimes are achieved by means of optimized particle fueling conditions at high input power, current, and magnetic field, which lead to a self-organized state with a strong increase in rotation and ion temperature and a decrease in the edge density. An interplay between core and edge plasma regions leads to reduced turbulence levels and outward impurity convection. These results pave the way to an attractive alternative to the standard plasmas considered for fusion energy generation in a tokamak with a metallic wall environment such as the ones expected in ITER.& nbsp;Published under an exclusive license by AIP Publishing

The role of ETG modes in JET-ILW pedestals with varying levels of power and fuelling

We present the results of GENE gyrokinetic calculations based on a series of JET-ITER-like-wall (ILW) type I ELMy H-mode discharges operating with similar experimental inputs but at different levels of power and gas fuelling. We show that turbulence due to electron-temperature-gradient (ETGs) modes produces a significant amount of heat flux in four JET-ILW discharges, and, when combined with neoclassical simulations, is able to reproduce the experimental heat flux for the two low gas pulses. The simulations plausibly reproduce the high-gas heat fluxes as well, although power balance analysis is complicated by short ELM cycles. By independently varying the normalised temperature gradients (omega(T)(e)) and normalised density gradients (omega(ne )) around their experimental values, we demonstrate that it is the ratio of these two quantities eta(e) = omega(Te)/omega(ne) that determines the location of the peak in the ETG growth rate and heat flux spectra. The heat flux increases rapidly as eta(e) increases above the experimental point, suggesting that ETGs limit the temperature gradient in these pulses. When quantities are normalised using the minor radius, only increases in omega(Te) produce appreciable increases in the ETG growth rates, as well as the largest increases in turbulent heat flux which follow scalings similar to that of critical balance theory. However, when the heat flux is normalised to the electron gyro-Bohm heat flux using the temperature gradient scale length L-Te, it follows a linear trend in correspondence with previous work by different authors

Testing a prediction model for the H-mode density pedestal against JET-ILW pedestals

The neutral ionisation model proposed by Groebner et al (2002 Phys. Plasmas 9 2134) to determine the plasma density profile in the H-mode pedestal, is extended to include charge exchange processes in the pedestal stimulated by the ideas of Mahdavi et al (2003 Phys. Plasmas 10 3984). The model is then tested against JET H-mode pedestal data, both in a 'standalone' version using experimental temperature profiles and also by incorporating it in the Europed version of EPED. The model is able to predict the density pedestal over a wide range of conditions with good accuracy. It is also able to predict the experimentally observed isotope effect on the density pedestal that eludes simpler neutral ionization models