Detecção de pessoas e dispositivos utilizando Channel State Information: IDS com features de camada física

• Eduardo Fabrício Gomes Trindade ITA
• Felipe Silveira de Almeida ITA
• Lourenço Alves Pereira Junior ITA

DOI: https://doi.org/10.5753/sbrc.2024.1544

Resumo

Sistemas de Detecção de Intrusão em Redes (NIDS) têm sido amplamente desenvolvidos ao longo do tempo. No entanto, ataques sofisticados têm demandado camadas de proteção adicionais. Assim, este estudo propõe utilizar dados do Channel State Information (CSI) Wi-Fi com técnicas de aprendizado de máquina para detecção nas camadas física e de enlace, visando identificar tentativas de acesso não autorizado a uma rede Wi-Fi. O estudo analisa 70.513 instâncias coletadas em dois ambientes e identifica atividades consideradas maliciosas com 94,24% de precisão, utilizando o algoritmo RandomForest. Destaca-se como uma abordagem inovadora, explorando CSI e incorporando características das camadas 1 e 2 no contexto de NIDS.

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