DDSHP: Um Sistema para a Detecção de DDoS em IoT baseado no Parâmetro de Hurst e SDN

Detalhes bibliográficos
Ano de defesa: 2023
Autor(a) principal: Moraes, Jorge Magno Lopes
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
IoT
SDN
Link de acesso: http://repositorio.ufc.br/handle/riufc/75221
Resumo: Currently, the Internet of Things (IoT), a paradigm that connects objects to the Internet without human intervention, is constantly growing and increasingly becoming a part of our lives. However, a growing concern with IoT is its security. After all, due to its limited resources (memory, energy, and storage), an IoT network becomes a potential target for various attacks, with Distributed Denial of Service (DDoS) being one of the most common. This attack disrupts IoT services, prevents access by legitimate users, and renders the service unavailable. This unavailability can lead to disastrous consequences. In this scenario, it is necessary to develop solutions that protect IoT from this type of attack. Software-Defined Networking (SDN) is a paradigm that separates data and control planes, ensuring centralized control and a global view of a network. As such, it becomes an attractive concept for securing IoT. Furthermore, with the Hurst Parameter, commonly linked to self-similarity, it is possible to detect DDoS attacks, making it an ideal method for an IoT environment due to its lightweight nature. Therefore, in this work, we propose and present a system called DDoS Detection System based on Hurst Parameter (DDSHP), which is an effort aimed at protecting the IoT network from DDoS attacks by applying SDN to IoT and using the Hurst parameter calculation to detect denial-of-service attacks. Through experiments, we show that this system is capable of detecting denial-of-service attacks with high efficiency in small IoT networks, such as smart homes, and exhibits a quick response time to attacks.