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Title: Detección de URLs fraudulentas mediante técnicas de aprendizaje automático
Author: Marin Batista, Brian Enrique
Director: Hernández Jiménez, Enric
Tutor: Rifà Pous, Helena  
Keywords: detection
machine learning
phishing URL
Issue Date: 2-Jun-2020
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: Currently within computer systems, data represents a very valuable and important asset for companies, institutions and governments. This means that there are more and more computer crimes that try to steal, impersonate and sell this highly valued data on the market. Therefore, it is found that the main focus of attackers and one of the most effective methods of information theft are phishing techniques that involve the use of social engineering. So the following Master's Thesis is aimed at using machine learning techniques that make use of classification algorithms, in order to determine when a URL is fraudulent or legitimate.
Language: Spanish
Appears in Collections:Bachelor thesis, research projects, etc.

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