Phishing websites detection using a novel multipurpose dataset and web technologies features

[EN] Phishing attacks are one of the most challenging social engineering cyberattacks due to the large amount of entities involved in online transactions and services. In these attacks, criminals deceive users to hijack their credentials or sensitive data through a login form which replicates the original website and submits the data to a malicious server. Many anti-phishing techniques have been developed in recent years, using different resource such as the URL and HTML code from legitimate index websites and phishing ones. These techniques have some limitations when predicting legitimate login websites, since, usually, no login forms are present in the legitimate class used for training the proposed model. Hence, in this work we present a methodology for phishing website detection in real scenarios, which uses URL, HTML, and web technology features. Since there is not any updated and multipurpose dataset for this task, we crafted the Phishing Index Login Websites Dataset (PILWD), an offline phishing dataset composed of 134,000 verified samples, that offers to researchers a wide variety of data to test and compare their approaches. Since approximately three-quarters of collected phishing samples request the introduction of credentials, we decided to crawl legitimate login websites to match the phishing standpoint. The developed approach is independent of third party services and the method relies on a new set of features used for the very first time in this problem, some of them extracted from the web technologies used by the on each specific website. Experimental results show that phishing websites can be detected with 97.95% accuracy using a LightGBM classifier and the complete set of the 54 features selected, when it was evaluated on PILWD dataset.SIINCIBEUniversidad de Leó

Nutritional Characteristics of the Seed Protein in 23 Mediterranean Legumes

The search for new sources of plant protein for food and animal feed is driven by an increasing demand in developing countries and the interest in healthy alternatives to animal protein. Seeds from 23 different wild legumes belonging to tribes Gallegeae, Trifolieae, and Loteae were collected in southern Spain and their total amino acid composition was analyzed, by reverse phase-high performance liquid chromatography (RP-HPLC), in order to explore their nutritional value. Protein content in the seeds ranged from 15.5% in Tripodium tetraphyllum to 37.9% and 41.3% in Medicago minima and Medicago polymorpha, respectively. Species belonging to tribe Trifolieae, such as Melilotus elegans and Trifolium spp., showed the most equilibrated amino acid composition and the best theoretical nutritional values, although all species were deficient in sulfur amino acids. The amino acid composition of the seeds from some of these legumes was characterized by high levels of the anticancer non-proteic amino acid canavanine This amino acid was found free in the seeds from some of the species belonging to each of the three tribes included in the present work. Astragalus pelecinus in tribe Gallegea, Trifolium angustifolium in tribe Trifolieae, and Anthyllis vulneraria in tribe Loteae have 3.2%, 3.7%, and 7.2% canavanine, respectively. Seeds from Anthyllis vulneraria, Hymenocarpus lotoides, and Hymenocarpos cornicina have the highest contents in canavanine overall. In conclusion, the seeds from some of these legumes could be used for human consumption and for feeding animals because they contain protein of good nutritional quality. These plants could be useful in domestication and breeding programs for production of new varieties with improved nutritional and functional properties. In addition, some of these species may be of interest as a source of the bioactive compound canavanineinfo:eu-repo/semantics/publishedVersio

Nonparametric estimation of the multivariate Spearman's footrule: A further discussion

Producción CientíficaIn this paper, we propose two new estimators of the multivariate rank correlation coefficient Spearman's footrule which are based on two general estimators for Average Orthant Dependence measures. We compare the new proposals with a previous estimator existing in the literature and show that the three estimators are asymptotically equivalent, but, in small samples, one of the proposed estimators outperforms the others. We also analyse Pitman efficiency of these indices to test for multivariate independence as compared to multivariate versions of Kendall's tau and Spearman's rho.Ministerio de Ciencia e Innovación (PID2020-113350GB-I00 y PID2021-122657OB-I00)Severo Ochoa Programme for Centres of Excellence in R&D (CEX2019-000904-S)FEDER-Andalucía 2014-2020 (UAL2020-AGR-B1783

A Framework for the Optimization of Complex Cyber-Physical Systems via Directed Acyclic Graph

[EN] Mathematical modeling and data-driven methodologies are frequently required to optimize industrial processes in the context of Cyber-Physical Systems (CPS). This paper introduces the PipeGraph software library, an open-source python toolbox for easing the creation of machine learning models by using Directed Acyclic Graph (DAG)-like implementations that can be used for CPS. scikit-learn’s Pipeline is a very useful tool to bind a sequence of transformers and a final estimator in a single unit capable of working itself as an estimator. It sequentially assembles several steps that can be cross-validated together while setting different parameters. Steps encapsulation secures the experiment from data leakage during the training phase. The scientific goal of PipeGraph is to extend the concept of Pipeline by using a graph structure that can handle scikit-learn’s objects in DAG layouts. It allows performing diverse operations, instead of only transformations, following the topological ordering of the steps in the graph; it provides access to all the data generated along the intermediate steps; and it is compatible with GridSearchCV function to tune the hyperparameters of the steps. It is also not limited to (�����,�����) entries. Moreover, it has been proposed as part of the scikit-learn-contrib supported project, and is fully compatible with scikit-learn. Documentation and unitary tests are publicly available together with the source code. Two case studies are analyzed in which PipeGraph proves to be essential in improving CPS modeling and optimization: the first is about the optimization of a heat exchange management system, and the second deals with the detection of anomalies in manufacturing processes.SIEspaña : Ministerio de Economía y Competitividad : grant number DPI2016-79960-C3-2-PMCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe

Improve Quality of Service for the Internet of Things using Blockchain & Machine Learning Algorithms.

[EN] The quality of service (QoS) parameters in IoT applications plays a prominent role in determining the performance of an application. Considering the significance and popularity of IoT systems, it can be predicted that the number of users and IoT devices are going to increase exponentially shortly. Therefore, it is extremely important to improve the QoS provided by IoT applications to increase their adaptability. Majority of the IoT systems are characterized by their heterogeneous and diverse nature. It is challenging for these systems to provide high-quality access to all the connecting devices with uninterrupted connectivity. Considering their heterogeneity, it is equally difficult to achieve better QoS parameters. Artificial intelligence-based machine learning (ML) tools are considered a potential tool for improving the QoS parameters in IoT applications. This research proposes a novel approach for enhancing QoS parameters in IoT using ML and Blockchain techniques. The IoT network with Blockchain technology is simulated using an NS2 simulator. Different QoS parameters such as delay, throughput, packet delivery ratio, and packet drop are analyzed. The obtained QoS values are classified using different ML models such as Naive Bayes (NB), Decision Tree (DT), and Ensemble, learning techniques. Results show that the Ensemble classifier achieves the highest classification accuracy of 83.74% compared to NB and DT classifiers.SIPublicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCL

A comprehensive approach to antioxidant activity in the seeds of wild legume species of tribe fabeae

The benefits of polyphenols have been widely demonstrated in recent decades. In order to find new species with a high biological functionality, the antioxidant activity of the polyphenol extracts from seeds of 50 taxa of tribe Fabeae (Lathyrus, Lens, Pisum, and Vicia) fromSpain has been studied. Considering the average concentration obtained fromthe data in the four genera of the Fabeae tribe, Pisum and Lathyrus show the highest average polyphenol concentration. The highest specific antioxidant activity as well as the antioxidant activity coefficient was observed in Pisum and Vicia. However, with respect to the total antioxidant activity, the highest average value was observed in Lathyrus and Pisum.The results obtained reveal that many of the wild taxa examined could be potential source of antioxidant

A fault detection system for a geothermal heat exchanger sensor based on intelligent techniques

[Abstract ]:This paper proposes a methodology for dealing with an issue of crucial practical importance in real engineering systems such as fault detection and recovery of a sensor. The main goal is to define a strategy to identify a malfunctioning sensor and to establish the correct measurement value in those cases. As study case, we use the data collected from a geothermal heat exchanger installed as part of the heat pump installation in a bioclimatic house. The sensor behaviour is modeled by using six different machine learning techniques: Random decision forests, gradient boosting, extremely randomized trees, adaptive boosting, k-nearest neighbors, and shallow neural networks. The achieved results suggest that this methodology is a very satisfactory solution for this kind of systems.Junta de Castilla y León; LE078G18. UXXI2018/000149. U-220.Ministerio de Economía, Industria y Competitividad; DPI2016-79960-C3-2-

Determination of -Cyano-L-alanine, -Glutamyl--cyano-L-alanine, and Common Free Amino Acids in Vicia sativa (Fabaceae) Seeds by Reversed-Phase High-Performance Liquid Chromatography

A method for determination of -cyano-L-alanine, -glutamyl--cyano-L-alanine and other free amino acids in Vicia sativa is presented. Seed extracts were derivatized by reaction with diethyl ethoxymethylenemalonate and analyzed by reverse-phase highperformance liquid chromatography. Calibration curves showed very good linearity of the response. The limit of detection and quantification was 0.15 and 0.50 M, respectively. The method has high intra-(RSD = 0.28-0.31%) and interrepeatability (RSD = 2.76-3.08%) and remarkable accuracy with a 99% recovery in spiked samples. The method is very easy to carry out and allows for ready analysis of large number of samples using very basic HPLC equipment because the derivatized samples are very stable and have very good chromatographic properties. The method has been applied to the determination of -glutamyl--cyano-L-alanine, -cyano-L-alanine, and common free amino acids in eight wild populations of V. sativa from southwestern Spain

An intelligent system for harmonic distortions detection in wind generator power electronic devices

The high concern about climate change has boosted the promotion of renewable energy systems, being the wind power one of the key generation possibilities in this field. In this context, with the aim of ensuring the energy efficiency, the present work deals with the fault detection in the power electronic circuits of a wind generator system placed in a bioclimatic house. To do so, different outliers that emulate harmonic distortion appearance are tested. To implement a system capable of detecting this anomalous situations, six different one-class techniques are used, whose performance is thoroughly analyzed, offering interesting performance.info:eu-repo/semantics/publishedVersio

Reacción de 1-amino-1-desoxi-D-arabino(lixo)-hexulosas y 1-alquil(aril)amino-1-desoxi-D-arabino(lixo)-hexulosas con cianamida

En esta Tesis Doctoral se estudia la reacción de 1-amino-1-desoxi-D-hexulosas y de 1-alquil(aril)amino-1-desoxi-hexulosas con cianamida, con el fin de obtener 2-imino-4-(tetritol-1-il)-2H-imidazoles y generalizar la reacción de la 2-amino-2-desoxi-D-glucosa con cianamida, estudiada por K. Odo y col., y por J. Yoshimura y col., que condujo a la obtención de iminoimidazoles polihidroxilados. En el primer apartado de la Tesis se estudia la reacción de las 1-amino-1-desoxi-D-arabino(lixo)-hexulosas con cianamida que conduce a 1,3-dihidro-2-imino-4-(D-arabino(lixo)-tetritol-1-il)-2HÇ-imidazoles, aislados como picratos (1 y 3) e hidrocloruros (2 y 4). Se describe la reacción de 1-alquil(aril) amino-1-desoxi-D-arabino(lixo)-hexulosas con cianamida mediante la cual se obtiene 1-alquil-1,3-dihidro-2-imino-4-(D-arabino(lixo)-tetritol-1-il)-2H-imidazoles, que se aíslan como picratos (7-11) (17-20) e hidrocloruros (12-16) (21-24), y 2-amino-1-aril-4-(D-arabino-tetritol-1-il)-1H-imidazoles (35-37). El tratamiento de 2-amino-1-aril-4-(D-arabino-tetritol-1-il)-1H-imidazoles (35-37) con ácido pícrico y ácido clorhídrico conduce a sus correspondientes iminoimidazoles polihidroxilados, que se aíslan como picratos (38-40) e hidrocloruros (41-43). Las estructuras de estos compuestos y de los derivados acetilados (5-6, 25-33, 44-46) se han asignado de acuerdo con los datos de sus análisis elementales, estudios de polarimetría, espectroscopía de UV, IR, 1H-RMN, 13C-RMN y espectrometría de masas. El estudio estereoquímico realizado a través de las constantes de acoplamiento medidas sobre los espectros de 1H-RMN, ha permitido conocer las conformaciones preferentes en solución de las cadenas poliólicas acetiladas de configuración D-arabino y D-lixo. Posteriormente se estudia la anhidrazación en medio –acido del hidrocloruro de 1,3-dihidro-2-imino-1-metil-4-(D-arabino-tetritol-1-il)-2H-imidazol (12) que permite la obtención de 4-(β-D-eritro-furanosil)-1,3-dihidro-2-imino-1-metil-2H-imidazol, que se aisla como picrato (48) e hidrocloruro (49). La estructura poliólica de estos iminoimidazoles es también la apropiada para obtener los correspondientes imino y amino 2H (ó 1H)-imidazol-4-carbaldehidos, por degradación oxidativa de la cadena de azúcar con metaperyodato sódico. De esta manera se han obtenido 1,3-dihidro-2-imino-2H-imidazol-4-carbaldehido (50) por oxidación del compuesto 2 y 1-alquil(aril)-2-amino-1H-imidazol-4-carbaldehidos (51, 53-55) por oxidación de los compuestos 12 y 35-37. Estos formilderivados del imidazol, no descritos en la bibliografía, tienen utilidad sintética ya que al poseer un grupo formilo conjugado con un sistema heterocíclico, son susceptibles de ser transformados en una variada gama de derivados del imidazol. Sus estructuras están de acuerdo con los datos del análisis elemental, espectroscopía de UV, IR y 1H-RMN. Los gluciiminoimidazoles preparados en esta Tesis Doctoral son compuestos que consideramos de interés farmacológico dada su analogía estructural con derivados del imidazol que presentan actividades anticancerosas, radioprotectoras, inmunosupresoras y antitiroideas