Classificação de URLs maliciosos by Jo Simon Ambata
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Classificação de URLs maliciosos

Classificação de URLs maliciosos


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About the Book

Este livro visa desenvolver um modelo que classifica se um determinado sítio web é legítimo ou malicioso utilizando metodologias de aprendizagem de máquinas e determinar se o aumento do conjunto de características de um modelo levará a um aumento do seu desempenho. Os autores utilizaram três casos distintos para gerar um modelo óptimo, cada caso difere no número de características utilizadas no conjunto de dados. O primeiro caso utilizou a base ou o conjunto de dados original. O segundo caso utilizou um conjunto alargado de características. Foi utilizado um algoritmo de selecção de características no conjunto alargado de características para criar um novo conjunto de dados para o terceiro caso. Os classificadores utilizados para gerar os modelos são Random Forest, J48, C-SVC, e kNN. O resultado mostrou um aumento no desempenho ao comparar os modelos do primeiro caso versus o segundo caso. Não foi observada qualquer alteração significativa quando os modelos do segundo caso foram comparados com os modelos do terceiro caso. O estudo mostrou que existe uma relação directamente proporcional entre o número de características de um modelo e o desempenho de um modelo. O aumento do número de características do conjunto de dados leva a um aumento do desempenho de cada modelo.


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Product Details
  • ISBN-13: 9786205307458
  • Publisher: KS Omniscriptum Publishing
  • Publisher Imprint: Edicoes Nosso Conhecimento
  • Height: 229 mm
  • No of Pages: 176
  • Spine Width: 10 mm
  • Width: 152 mm
  • ISBN-10: 6205307456
  • Publisher Date: 04 Nov 2022
  • Binding: Paperback
  • Language: Portuguese
  • Returnable: N
  • Weight: 317 gr


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