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Several threats are propagated by malicious websites largely classified as phishing. Its function is important information for users with the purpose of criminal practice. In summary, phishing is a technique used on the Internet by criminals for online fraud. The Artificial Neural Networks (ANN) are computational models inspired by the structure of the brain and aim to simulate human behavior, such as learning, association, generalization and abstraction when subjected to training. In this paper, an ANN Multilayer Perceptron (MLP) type was applied for websites classification with phishing characteristics. The results obtained encourage the application of an ANN-MLP in the classification of websites with phishing characteristics.

A Filosofia Lean é uma estratégia de negócios utilizada para aumentar a satisfação dos clientes, através da melhor utilização dos recursos da empresa. O êxito na sua aplicação tem uma forte dependência cultural devido o envolvimento das pessoas e na melhoria contínua dos processos internos da organização. Neste contexto, este artigo teve por objetivo analisar a relação entre a Filosofia Lean e a Cultura Organizacional, por meio de uma revisão sistemática da literatura amparada por um estudo bibliométrico para avaliar a aplicação da Filosofia Lean na Cultura Organizacional. As buscas foram realizadas nas bases digitais Web Of Science e Scopus dentro de um período de 10 anos, e analisados os comportamentos bibliométricos existentes entre os dois temas. Foi utilizada uma pesquisa qualitativa e quantitativa com uso de estatística para medir índices de produção acadêmica, bem como analisado o desenvolvimento da Cultura Organizacional e a Filosofia Lean, enquanto áreas de pesquisa científica, relacionadas por meio da evolução das publicações. Os resultados encontrados evidenciam uma relação entre as duas áreas conforme verificado nos resultados dessa pesquisa a Cultura Organizacional é um tema mais antigo e que norteia a forma como as organizações se comportam, entretanto, após o surgimento da Filosofia Lean, pode ser percebido que os autores desses dois assuntos se citam e se relacionam demostrando que a Filosofia Lean pode ser associada à Cultura Organizacional de forma que passe a moldá-la para benefício do cliente.

Purposeinvestigate and analyze the aspects of legitimation, theorization and trends for the evolution of research in information technology governance (ITG) in Brazil, according to researchers familiar with the matter.Design/methodology/approachBy means of a qualitative and quantitative research of exploratory-descriptive approach, the Delphi method was applied using a questionnaire supported by content analysis.FindingsITG is an increasingly interdisciplinary research field, with significant help from other fields of knowledge, such as administration, computer science and engineering. The main means of ITG publication are periodicals (MISQ, JMIS, JISTEM RESI), scientific events (AMCIS, ECIS, HICSS, EnANPAD, CONTECSI) and researchers, such as Peter Weill and Edimara Mezzomo Luciano. Best practice models are the most significant theoretical frameworks, and the main trend of research are on emerging technologies such as cloud computing and Internet of things (IoT) in the context of ITG.Research limitations/implicationsTo the unavailability of some researchers to participate in the second phase of the Delphi research performed, as well as the non-completion of a third Delphi round. Likewise, the “Block B (open answer questions)” it was not contemplated in the second phase for a new collection of answers, which could partially change the results presented here.Practical implicationsThe results show important insights for ITG researchers that can allow new researches about its applications, jointly reflecting on relevant aspects for the advancement of this research field.Social implicationsThere are several research contributions to broaden the discussion and the evolution of this new scientific field in Brazil and that can be grouped for each set of stakeholders: academia and related researchers; the practicing community of business managers and private and public organizations; the academic legitimizing bodies; the non-academic legitimating bodies and researchers from other areas of knowledge.Originality/valueITG is a concept that emerged as part of corporate governance (CG), which has evolved as an emerging theme and is expanding in the international academic arena. However, the current stage of legitimation, theorization and trends of ITG in the Brazilian researches are lacked greater understanding, in order to provide better targeting for new researches.

The provision of credit to customers of banking chains through call center services has always been one of the resources that generate significant income for financial institutions, however, the service offers a cost, which is often above desirable to guarantee profitable contracting to Bank. Based on this, this work aims to evaluate the optimization of operational costs of call center, using classification techniques, through experimentation of supervised machine learning techniques to perform the classification task, in order to generate a predictive model, which offers a better performance in the operation of offering bank credit, to carry out an effective and productive action, conceiving greater savings for the company in identifying the public with greater adherence. For this, a database comprising 11,162 call records made from a bank offering its customers a letter of credit was employed. The results showed value correlations between variables, such as duration of the call, marital status, education level and even recurrence in adhering to subscribers' credit agreements. Through the application of the PCA to reduce dimensionality and classification models, such as AdaBoost, Gradient Boosting, SVM RBF, Naive Bayes, Random Forest, it was possible to perceive the consumer profile with good acquiescence for the investment proposal and a group of people with a high probability of not adhering to the letter of credit, so it was possible to outline an action directed to the public predisposed to the offer, minimizing expenses reaching greater profitability.

Projects are essential for organizations to transform strategies into results, but uncertain events can impose risks to achieve a certain objective. Risk management aims to support an organization in deciding how to deal with risks, prioritizing them through the application of Risk Matrices (RMs). RMs or Probability and Impact Matrices is used to support decision-making, helping management to classify and prioritize risks to decide which will be ad-dressed, monitored, or tolerated. RMs are supposedly easy to build and explain, but according to the literature they may contain uncertainties. To deal with uncertainty, it is recommended to apply a Fuzzy Inference System, based on Fuzzy Set Theory (FST) or a Fuzzy Neural Inference System with the presence of an artificial neural network. Thus, the aim of this paper was to develop and apply a Fuzzy Inference System (FIS) and a Fuzzy Neural Inference System (FNIS) in the classification of MRs in projects to reduce uncertainty. The analysis of the results indicated that the application of the two systems resulted in a continuous classification rule by smoothing the boundary areas between each of the RM classes, reducing uncertainty and improving risk classification. Both systems showed good results in reducing uncertainty. However, the results obtained with FNIS were more consistent. The main contribution of this work lies in the possibility of improving the decision making by reducing the uncertainty present in RMs.

O objetivo deste artigo é aplicar inteligência computacional com técnicas de data mining para identificar através da tarefa de clusterização e classificação o perfil de empregados absenteístas e presenteístas, utilizando o algoritmo Density Based Spatial Clustering of Applications With Noise (DBSCAN) e Redes Neurais Artificiais (RNAs) na descoberta de conhecimento em base de dados. O Avanço da ciência computacional permite o processamento de grande quantidade de dados, o que motiva o estudo em questão, o termo data mining surgiu devido às semelhanças entre a procura de informação importante numa base de dados e o ato de minerar a montanha para encontrar um veio de ouro. Data mining é o elemento responsável pela extração eficiente do conhecimento implícito e útil contido em um banco de dados. O Absenteísmo é o não comparecimento ao trabalho, conforme o programado. No Presenteísmo há a presença do empregado no trabalho, ainda que doente, contudo, suas atividades são improdutivas. O algoritmo DBSCAN foi aplicado em data mining para clusterizar e a RNA foi aplicada para classificar níveis de perfis absenteístas e presenteístas. Os resultados apresentados mostraram que a aplicação das técnicas no data mining foi satisfatória, o que confirma a utilização das técnicas como uma opção a ser utilizada neste tipo de problema. A metodologia adotada na estruturação deste artigo foi definida como bibliográfica, exploratória e experimental.

A influência da gestão de risco nos projetos é um campo de estudo que merece atenção de acadêmicos e profissionais em gerenciamento de projetos. Este trabalho apresenta os resultados de uma pesquisa sobre a influência do processo de identificação de riscos nas decisões de projetos. O método adotado foi a pesquisa tipo survey que envolveu 146 projetos do Brasil e Peru. Os resultados foram analisados por meio de métodos estatísticos, por meio de análise de regressão, linear e logística, e as relações estudadas mostraram que os esforços no processo de identificação de riscos em projetos influenciaram de forma significativa as decisões nos projetos. Foi possível verificar que os gerentes de projetos fizeram uso das informações obtidas do processo de identificação de riscos para a tomada de decisão.