Venancio Neto, Augusto JoseCabral, Jhonattan Carlos Barbosa2024-07-092024-07-092024-06-20CABRAL, Jhonattan Carlos Barbosa. Sistema preditivo de detecção de intrusão em redes definidas por software por múltiplas técnicas de aprendizado de máquina. Orientador: Augusto Jose Venancio Neto. 2024. 62 f. Trabalho de Conclusão de Curso (Bacharelado em Ciência da Computação) - Departamento de Informática e Matemática Aplicada, Universidade Federal do Rio Grande do Norte, Natal, RN, 2024.https://repositorio.ufrn.br/handle/123456789/58701With the evolution of the Internet of Things (IoT) and the current reality of fifthgeneration mobile network standards (5G), a strong demand for a large volume of data is expected. Additionally, aiming to achieve greater control flexibility in the network, studies focused on Software-Defined Networking (SDN) have been gaining increasing attention. With SDN, the network’s control plane is implemented in a centralized and unified manner within a controller. As 5G networks advance, leading to the emergence of highly innovative applications, it is expected that a significant amount of sensitive information will be transmitted through the network, making it essential to adopt security mechanisms capable of providing secure channels over SDNs and ensuring end-to-end data integrity. Despite enhancing the network through global visibility of its state, this introduces security challenges, as the controller may become a single point of failure, leading to chaos propagation and compromising the entire infrastructure. This work proposes to deploy an Intrusion Detection System (IDS) in the context of SDN making use of Machine Learning techniques. The goal of the study is to enhance the security of communication channels by identifying multiple ML techniques that best fit into the intrusion detection over SDNs.CC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/ComputaçãoAprendizado de máquinaRedes definidas por softwareSegurança cibernéticaSistema de detecção de intrusãoMachine learningSoftware-defined networkingCyber securityIntrusion detection systembachelorThesis