Aplicabilidade e Impactos quanto a Adoção de Modelos de Classificação como Mecanismos Anti-phishing.

  • Mateus de Barros UFRPE
  • Carlo da Silva UPE
  • Péricles de Miranda UFRPE


Phishing websites are fake addresses that cheat the victims, passing by legitimate sites from banks or companies to obtain personal information without their consent. Looking to solve this problematic, several ways of defense were put into practice, among them the Machine Learning (ML). This article presents an study about ML utilization on malicious websites detection, reporting the methods used and concluding about their impact on precision and relevance.


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DE BARROS, Mateus; DA SILVA, Carlo; DE MIRANDA, Péricles. Aplicabilidade e Impactos quanto a Adoção de Modelos de Classificação como Mecanismos Anti-phishing.. In: WORKSHOP DE TRABALHOS DE INICIAÇÃO CIENTÍFICA E DE GRADUAÇÃO - SIMPÓSIO BRASILEIRO DE SEGURANÇA DA INFORMAÇÃO E DE SISTEMAS COMPUTACIONAIS (SBSEG), 19. , 2019, São Paulo. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2019 . p. 39-42. DOI: https://doi.org/10.5753/sbseg_estendido.2019.14003.