TCC - Bacharelado em Ciência da Computação (Sede)
URI permanente para esta coleçãohttps://arandu.ufrpe.br/handle/123456789/415
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Resultados da Pesquisa
Item Comparação de VPN e ZTNA: uma análise de segurança e desempenho em ambientes corporativo(2024-09-30) Chagas, Marcelino Francisco Gomes das; Medeiros, Robson Wagner Albuquerque de; http://lattes.cnpq.br/3169193612606500Constant technological advances and the rapid expansion of infrastructures in public cloud providers have created significant challenges for companies, especially with regard to information security. Traditional security measures, such as Virtual Private Networks (VPNs), which create a secure tunnel for data transmission between the user and the corporate network, are not always adequate to protect data in cloud environments, resulting in a growing need to re-evaluate protection strategies. The COVID-19 pandemic has further intensified this demand, as organizations have been forced to adopt remote working practices on a large scale. In this scenario, trust in the final data has become a critical concern, especially given the limitations of traditional VPN solutions. In response to these challenges, Zero Trust Architecture (ZTA) and Zero Trust Network Access (ZTNA) have emerged as promising approaches. ZTNA is a technology based on the principles of ZTA that redefines network access control by eliminating implicit trust in any user or device, regardless of their location, and requiring continuous verification for every access attempt. This approach offers more granular security at the network and access control level, and is adaptable in on-premise and cloud environments, protecting data in distributed and constantly evolving corporate environments. The aim of this work is to carry out a comparative analysis of VPN and ZTNA network technologies, with an emphasis on evaluating security and performance. The security features offered by each technology will be examined, including authentication, access control and encryption, as well as the impact of these technologies on network performance in terms of latency, bandwidth and response time. Through this analysis, we aim to identify the advantages and disadvantages of each technological approach, offering valuable insights for IT professionals and organizations in selecting and implementing the solution best suited to their security and performance needs in modern corporate environments.Item Uma metodologia para a avaliação de desempenho e custos do treinamento de redes neurais em ambientes de nuvem(2024-03-07) Moura Filho, Cláudio Márcio de Araújo; Sousa, Érica Teixeira Gomes de; http://lattes.cnpq.br/9899077867723655; http://lattes.cnpq.br/8143173691280119Deep neural networks are solutions to problems involving pattern recognition and several works try to find ways to optimize the performance of these networks. This optimization requires suitable hardware to be implemented, hardware that can be very expensive for small and medium-sized organizations. The objective of this work is to propose a methodology to evaluate the performance and cost of training neural networks, considering the factors that most impact training time and evaluate the total financial cost of the environment for this task. In this sense, it was observed that factors such as the size of the input image and the network architecture have a great impact on the training time metric and consequently on the total cost.Item Uma análise do impacto das linguagens de programação nos custos de execução no AWS Lambda em cenários de cold start e warm start(2023-04-24) Andrade Júnior, Edilson Alves de; Medeiros, Robson Wagner Albuquerque de; http://lattes.cnpq.br/3169193612606500; http://lattes.cnpq.br/5131828050788518Public cloud computing solutions have gained visibility on the market for offering great advantages over on-premises systems. However, cloud-based management workflows also brings concerns. As well as problems related to information security and lack of skilled professionals, cost management is one of the main challenges faced by users and organizations that migrate or already have their operations on cloud. Cloud providers define variables that directly affect cost behaviors, in addition, factors such as key characteristics of programming languages can also contribute to change those behaviors. This work aimed to understand how programming languages behave in cloud services such as AWS Lambda, so that cost management is carried out more assertively and efficiently, directly contributing to the reduction of costs and financial waste when using this kind of service. The results showed that the characteristics of programming languages significantly interfere in the financial costs of execution, elucidating that the choice of a certain programming language should be considered when cost is a requirement to be met when using AWS Lambda.