Estimativa de Distância em Redes Wi-Fi usando Super-sniffers

  • Pedro Videira Rubinstein UFRJ
  • Fernando Dias de Mello Silva UFRJ
  • Mohammad Imran Syed Sorbonne Université / CNRS / LIP6
  • Anne Fladenmuller Sorbonne Université / CNRS / LIP6
  • Marcelo Dias de Amorim Sorbonne Université / CNRS / LIP6
  • Luís Henrique M. K. Costa UFRJ

Resumo


Sniffers Wi-Fi são dispositivos responsáveis por realizar a coleta passiva de pacotes em redes sem-fio. Sniffers possuem aplicações, entre outras, em processos de estimativa de distância e localização através do uso da métrica RSSI (Received Signal Strength Indicator). Porém, o RSSI é sensível a pequenas pertubações no ambiente e, sem tratamento, não fornece uma estimação de distância confiável. Este artigo formula uma nova abordagem que utiliza redundância através de um super-sniffer que consiste de múltiplos sniffers colocalizados para melhorar o processo de classificação de distância através de dois modelos, baseados em k-Nearest Neighbors (k-NN) e em log-distance path loss (LDPL). Aplica-se a estratégia formulada a um conjunto de dados experimental próprio e mostra-se que o método é capaz de gerar um modelo com acurácia média de 91,73%, além de determinar um ponto de saturação para os ganhos relacionados ao aumento do tamanho do super-sniffer.

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Publicado
20/05/2024
RUBINSTEIN, Pedro Videira; SILVA, Fernando Dias de Mello; SYED, Mohammad Imran; FLADENMULLER, Anne; AMORIM, Marcelo Dias de; COSTA, Luís Henrique M. K.. Estimativa de Distância em Redes Wi-Fi usando Super-sniffers. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 42. , 2024, Niterói/RJ. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2024 . p. 503-516. ISSN 2177-9384. DOI: https://doi.org/10.5753/sbrc.2024.1428.

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