Autoproteção para a internet das coisas

• Ano de defesa: 2016
• Autor(a) principal: Almeida, Fernando Mendonça de
• Orientador(a): Ribeiro, Admilson de Ribamar Lima
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Sergipe
• Programa de Pós-Graduação: Pós-Graduação em Ciência da Computação
• País: Brasil
• Palavras-chave em Português: Computação; Internet; Internet das coisas; Redes neurais (Computação); Algoritmos de computador; Autoproteção; Redes neurais artificiais; Algoritmo de células dendríticas
• Palavras-chave em Inglês: Internet of things; Self-protection; Artificial neural networks; Dendritic cells algorithm
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: https://ri.ufs.br/handle/riufs/3361

The Internet of Things is a new paradigm of communication based on the ubiquitous presence of objects that, having unique address, they can cooperate with their peers to achieve a common goal. Applications in several areas can benefit from this new paradigm, but the Internet of Things is very vulnerable to attack. The large number of connected devices make an autonomic approach necessary and the small amount of resources requires the use of efficient techniques. This paper proposes a self-protection architecture for the Internet of Things using Artificial Neural Network and Dendritic Cells Algorithm, two bio-inspired techniques. The experiments of this paper show that the use of these two techniques is possible. The Artificial Neural Network implementation consume a small memory footprint, having a high accuracy rate and the Dendritic Cells Algorithm show to be interesting for it distributivity, allowing better use of network resources.