TCC - Bacharelado em Sistemas da Informação (Sede)
URI permanente para esta coleçãohttps://arandu.ufrpe.br/handle/123456789/427
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Item Desenvolvimento de uma artefato para aprendizado sobre segurança da informação em APIs(2023-05-15) Castro, Ricardo Henrique Rodrigues de; Assad, Rodrigo Elia; http://lattes.cnpq.br/3791808485485116In today’s world, Application Programming Interfaces (APIs) play a crucial role in applications by enabling integration between different systems. However, due to the sensitivity of the data and personal information that APIs handle, they are often targeted by malicious actors. To assist developers and security analysts, the Open Web Application Security Project (OWASP) has published a list of the top ten most common API security problems, aiming to identify and provide guidance on resolving them. In this context, this article proposes an innovative approach to learning security in APIs, utilizing the problem-based learning method known as Problem-Based Learning (PBL). This approach will actively engage students in solving real challenges related to API security, exposing them to authentic problems and developing practical skills in analysis, vulnerability identification, and countermeasure application.Item QA Metrics: integração das métricas de qualidade de software, em ambiente Docker, para exibição de dashboards Grafana alimentado pelo banco de dados temporal InfluxDB via Newman(2022-07-15) Silva, Lucas Ferreira da; Bocanegra, Silvana; Assad, Rodrigo Elia; http://lattes.cnpq.br/3791808485485116; http://lattes.cnpq.br/4596111202208863; http://lattes.cnpq.br/9075508106025707Software Quality metrics and indicators are able to help a software tester, commonly known as QA, to assess what needs to be done to improve performance of a software development project. In addition, it makes it possible to monitor the progress of a project in order to suggest initiatives based on the collected data. However, gathering the metrics obtained from different data sources to present them in real time is not an easy task for some companies. Nevertheless, with the use of APIs, it is possible to collect the data, analyze and present them in dashboards and reduce QA rework. In this paper, it was developed a system capable of collecting data from three services in order to present, in dashboards, the metrics that are essential in the area of Software Quality. Furthermore, the collection and storage of these metrics are performed in an automated and orchestrated manner through a compact, fast, efficient, safe, portable and isolated application.Item Sistema para detecção de intrusão de botnets utilizando aplicações de machine learning(2021-12-13) Silva Neto, Francisco Queiroga da; Assad, Rodrigo Elia; http://lattes.cnpq.br/3791808485485116; http://lattes.cnpq.br/7900008638092251Communication tools and the continuous advancement of the Internet have also resulted in the sophistication of tools and methods to carry out attacks against users and their computers, with features that facilitate criminal activities in the cyber environment. Among cyber threats, botnets have characteristics and advantages that have expanded their use in recent years, becoming a tool employed extensively by attackers to conduct attacks and gain control of various devices connected to computer networks. The way these threats behave and are updated brings several challenges to the intrusion detection area. In this paper, a study is presented on the application of machine learning techniques in detecting botnets by analyzing network traffic flows. The study aims to show how pattern classification techniques can be applied in intrusion detection systems to identify similarities between the infrastructure of botnets, where works in the literature were studied to address an application that aims to improve the problems related to the attribute selection steps and the data processing, crucial steps in machine learning models.