Modelagem e simulação para estimativa de risco de falha em redes IOT por meio de redes Bayesianas e método Monte Carlo

Detalhes bibliográficos
Ano de defesa: 2024
Autor(a) principal: Kinjo, Erika Midori lattes
Orientador(a): Librantz, Andre Felipe Henriques lattes
Banca de defesa: Librantz, Andre Felipe Henriques lattes, Martins, Fellipe Silva lattes, Souza, Edson Melo de lattes, Dias, Cleber Gustavo lattes, Araújo, Sidnei Alves de lattes
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Nove de Julho
Programa de Pós-Graduação: Programa de Pós-Graduação em Informática e Gestão do Conhecimento
Departamento: Informática
País: Brasil
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: http://bibliotecatede.uninove.br/handle/tede/3510
Resumo: The advancement of Internet of Things (IoT) technology has revolutionized several areas, such as: helping to monitor elderly people, improving classrooms, smart home automation, monitoring crops, among others. However, there are market researches that report worrying numbers regarding failures in the implementation of IoT projects, including failures that even make their use unfeasible. As a result, the subject of privacy and data security was highlighted as one of the most cited subjects in works in the area. So, in this scenario this work aims to contribute, by using Bayesian Networks combined with Monte Carlo to model a system that makes possible to simulate and measure risk in the internet of things network - IoT. The methodology used was a mixed approach, when applying the chosen methods. The model developed in this work included components external to the IoT network in a model already established in the representation of systems networks and was called OSI*. The lack of standardization when representing a network combined with the non-inclusion of external components corroborates the analysis of the criticality raised in this work. The model developed allowed us to evaluate the risk of failure of the IoT network in the context of data privacy and security.