Tracking Traitors in Web Services via Blind Signatures

This paper presents a method and its implementation, built on the blind signatures protocol, to trace users sharing their licenses illegally when accessing services provided through Internet (Web services, Streaming, etc). The method devised is able to identify the legitimate user from those users who are illegally accessing services with a shared key. This method is robust when detecting licenses built with no authorization. An enhancement of the protocol to identify the last usage of a certain license is also provided, allowing to detect a traitor when an unauthorized copy of a license is used

Teucrium aureum subsp. turdetanum Devesa & Valdés-Bermejo, subsp. nov.

In this paper a new taxon of the genus Teucrium from SW Spain is described, T. aureum subsp. turdetanum Devesa & Valdes-Bermejo.Se describe para el SW de España un nuevo taxon del género Teucrium, T. aureum subsp. turdetanum Devesa & Valdes-Bermejo

Systematic Approach for Web Protection Runtime Tools’ Effectiveness Analysis

Web applications represent one of the principal vehicles by which attackers gain access to an organization’s network or resources. Thus, different approaches to protect web applications have been proposed to date. Of them, the two major approaches are Web Application Firewalls (WAF) and Runtime Application Self Protection (RASP). It is, thus, essential to understand the differences and relative effectiveness of both these approaches for effective decision-making regarding the security of web applications. Here we present a comparative study between WAF and RASP simulated settings, with the aim to compare their effectiveness and efficiency against different categories of attacks. For this, we used computation of different metrics and sorted their results using F-Score index. We found that RASP tools scored better than WAF tools. In this study, we also developed a new experimental methodology for the objective evaluation of web protection tools since, to the best of our knowledge, no method specifically evaluates web protection tools

Análisis de Ruido en Reactores PWR

Esta tesis se ha llevado a cabo persiguiendo dos objetivos principales: uno de ellos es el desarrollo y la aplicación de modelos para el mantenimiento predictivo de sensores en centrales nucleares, y el otro es profundizar en el entendimiento de los fenómenos que tienen influencia en el ruido de la señal de los detectores de neutrones de los reactores de agua a presión con ayuda de herramientas de simulación 3D. Para el desarrollo de los trabajos se ha contado con medidas de ruido de reactores PWR actualmente en operación registradas en el curso de la tesis. El análisis de estas medidas ha permitido desarrollar los modelos de los sensores a partir de sus señales reales y comparar lo obtenido en las simulaciones con la realidad. El estudio de los sensores y la elaboración de los modelos se han llevado a cabo mediante la aplicación de técnicas autorregresivas a las señales tomadas en planta. Para la reproducción de los fenómenos que tienen lugar en el núcleo del reactor y que pueden influir en el ruido neutrónico se ha contado con códigos neutrónicos ampliamente utilizados en la industria y con modelos actualizados y validados de las plantas. ABSTRACT There are two goals in this thesis. The first one is the development of models and its application for predictive maintenance of sensors in nuclear power plants. The second one is to improve the understanding of the phenomena that influence the neutron noise in pressurized water reactors by using 3D simulators. Real plant measurements recorded during this thesis have been used to achieve such goals. The information provided by the data led the development of the models and the comparison of the results provided by the computational simulations. Sensor models were obtained by applying autorregresive techniques to the signals recorded in the plant. Wide known codes in the nuclear industry as well as updated and validated models have been used for the reproduction of the phenomena that take place in the core an may influence the neutron noise

Factores de riesgo cardiovascular y periodontitis

[ES] Se realizó un estudio sobre cien pacientes, portadores todos ellos de factores de riesgo cardiovascular y periodontitis crónica. Los pacientes estaban, durante largo tiempo, en tratamiento en prevención primaria o secundaria de sus factores de riesgo cardiovascular y visitaban regularmente a su odontólogo. Tratamos de averiguar si existían relaciones de causalidad o de casualidad entre ambas entidades clínicas. Para ello se estudiaron cuarenta y seis items de factores de riesgo cardiovascular de los pacientes. Todos los datos recogidos fueron trasladados a una hoja Excel y tratados mediante el programa estadístico SPSS. Se realizó en una primera fase un análisis descriptivo, determinando los valores medio, desviación típica e intervalos. Posteriormente se realizó una estadística inferencial, mediante la prueba de Chi cuadrado y la T de Student. Luego se realizó un análisis estadístico multivariante o Análisis de Segmentación o Árbol de Decisión/Clasificación. Y comprobamos que: Dado que todos los pacientes del estudio padecen algún tipo de periodontitis crónica y a la vez algún grado de riesgo cardiovascular, podemos decir que existe una relación entre la enfermedad aterosclerótica y la periodontitis crónica. Esta relación está por dilucidar si es causal o casual. Los pacientes tratados de forma continuada, en prevención primaria o secundaria, de riesgo cardiovascular presentan una menor profundidad de bolsa alveolar. Los pacientes con menor grado de periodontitis crónica tienen mejor control de sus factores de riesgo cardiovascular. Los pacientes con cifras elevadas de colesterol unido a lipoproteínas de alta densidad, presentan más profundidad de bolsa alveolar periodontal, por lo que, a la vez, los pacientes con mayor profundidad de bolsa alveolar se asocian más a una cifra de c- HDL elevado, lo que unido a lo expuesto en el trabajo podría expresar una vez más que el c-HDL elevado no confiere siempre protección cardiovascular. Los pacientes con periodontitis crónica leve se asocian más con riesgo cardiovascular bajo y los pacientes con periodontitis severa se asocian más con riesgo cardiovascular medio y alto. Cuando se efectúa cualquier tipo de actuación en cuanto a prevención cardiovascular, sea sobre los factores llamados clásicos o sobre los llamados emergentes, incluida la periodontitis crónica, incluso no alcanzando cifras de prevención según las guías europeas de cada entidad patológica, se mejora el pronóstico y el devenir vascular global de todos los pacientes en el contexto epidemiológico

Evaluation of leakages effects in the water supply system of Moratalla (Spain). Póster

One of the risk management requirements is the assessment of the effect of each kind of possible failure. In water supply systems, the most common failures are the pipe leakages. Most leakages can be modelled as orifices in a pipe [1]. At this paper, a leakage pattern is defined for each of the 300 pipes in Moratalla’s water supply system. That leakage pattern is defined as an orifice whose diameter length is 1/10 of the pipe diameter. Epanet-Octave is a GNU Octave wrapper that makes easy and vector oriented the use of EPANET ToolKit. Epanet-Octave library has been used to carry out a simulation for each pipe which may have a leakage. Each simulation lasts a whole simulated day to include leakage effects for the different pressures and demands that happen during the day. Then, the results are summarised by using an index which weights the negative effect of the leakages. Usually leakages are evaluated mainly by the energy waste in pumping that water [2-3]. In this case, the suggested index accounts for leakage flow rates, water quality deterioration and service deterioration. Leakage flow rates effects are included through the maximum leakage flow rate (in time) and its average value, which in this case is proportional to the energy cost used in other works as the system distributes the water from the reservoirs to customers by gravity. Water quality deterioration is evaluated by the presence of negative pressures around the orifice. Finally, service deterioration is measured through the water that would be supplied below the regulated minimum pressure. This weighted index, which is shown in figure 1, can be used, together with other non-hydraulic factors like pipe-age or pipe-material, to prioritise the maintenance and even the replacement of pipes according to a risk management strategy

Review and Comparison of Intelligent Optimization Modelling Techniques for Energy Forecasting and Condition-Based Maintenance in PV Plants

Within the field of soft computing, intelligent optimization modelling techniques include various major techniques in artificial intelligence. These techniques pretend to generate new business knowledge transforming sets of "raw data" into business value. One of the principal applications of these techniques is related to the design of predictive analytics for the improvement of advanced CBM (condition-based maintenance) strategies and energy production forecasting. These advanced techniques can be used to transform control system data, operational data and maintenance event data to failure diagnostic and prognostic knowledge and, ultimately, to derive expected energy generation. One of the systems where these techniques can be applied with massive potential impact are the legacy monitoring systems existing in solar PV energy generation plants. These systems produce a great amount of data over time, while at the same time they demand an important e ort in order to increase their performance through the use of more accurate predictive analytics to reduce production losses having a direct impact on ROI. How to choose the most suitable techniques to apply is one of the problems to address. This paper presents a review and a comparative analysis of six intelligent optimization modelling techniques, which have been applied on a PV plant case study, using the energy production forecast as the decision variable. The methodology proposed not only pretends to elicit the most accurate solution but also validates the results, in comparison with the di erent outputs for the di erent techniques

Proposals of a procedure to asses Pollutographs. Application to Murcia's Combined Sewer Overflows (CSOs). Póster

Directives 91/271/EEC and 93/481/EEC set norms regarding the management of Combined Sewer Overflows. European Commission monitors the implementation status and implementation programmes. In fact, during the year 2019 all the utilities should be able to quantify the pollution spilled during storm events. And afterwards, plans have to be developed in order to reduce the impact of such events. In this paper, we proposed a method to estimate the transported pollution during events as well as to serve as a tool for developing plans to lessen the corresponding pollution. The procedure is divided into three steps: A. Periodical measurements of all relevant pollutants, e.g. total suspended solids and chemical oxygen demand, in wet and dry weather. Such pollutant “concentrations” are correlated with the turbidity, updating the relation among them [1]. B. Continuous measures of the turbidity. Turbidity is continously register in the sewer areas near overflow spillways. Turbidimeters are a very convenient equipment for this purpose [2]. Actually, it is reliable, its measures are very correlated with the total suspended solid concentration and its maintenance is easy. In this way, combining A. and B. turbidity measures provide us a real-time estimation of the pollutant concentration. on real time. C. Assesment of each catchment hydrograph. Depending on the available data, this step could be based on a design, a measured or a simulated hydrograph. In order to apply this methodology to Murcia’s Combined Sewer System, we have used simulated hydrographs based on real measured rainfall. Murcia’s utility has developed a calibrated SWMM model, and therefore, using the rainfall data, it is possible to estimate hydrographs for all the relevant points of the system. D. Estimation of each catchment pollutograph. Combining the pollutant concentration, estimated in the previous steps, with the hydrographs, we can asses how the mass of pollutants are transported. This information allows us to comply with EU Directives, but it will also be useful to design Murcia’s strategy to minimize environmental impacts

A new multi-label dataset for Web attacks CAPEC classification using machine learning techniques

Context: There are many datasets for training and evaluating models to detect web attacks, labeling each request as normal or attack. Web attack protection tools must provide additional information on the type of attack detected, in a clear and simple way. Objectives: This paper presents a new multi-label dataset for classifying web attacks based on CAPEC classification, a new way of features extraction based on ASCII values, and the evaluation of several combinations of models and algorithms. Methods: Using a new way to extract features by computing the average of the sum of the ASCII values of each of the characters in each field that compose a web request, several combinations of algorithms (LightGBM and CatBoost) and multi-label classification models are evaluated, to provide a complete CAPEC classification of the web attacks that a system is suffering. The training and test data used for training and evaluating the models come from the new SR-BH 2020 multi-label dataset. Results: Calculating the average of the sum of the ASCII values of the different characters that make up a web request shows its usefulness for numeric encoding and feature extraction. The new SR-BH 2020 multi-label dataset allows the training and evaluation of multi-label classification models, also allowing the CAPEC classification of the various attacks that a web system is undergoing. The combination of the two-phase model with the MultiOutputClassifier module of the scikit-learn library, together with the CatBoost algorithm shows its superiority in classifying attacks in the different criticality scenarios. Conclusion: Experimental results indicate that the combination of machine learning algorithms and multi-phase models leads to improved prediction of web attacks. Also, the use of a multi-label dataset is suitable for training learning models that provide information about the type of attack. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/