Please use this identifier to cite or link to this item:
http://hdl.handle.net/10609/117926
Title: | Detección de URLs fraudulentas mediante técnicas de aprendizaje automático |
Author: | Marin Batista, Brian Enrique |
Director: | Hernández Jiménez, Enric |
Tutor: | Rifà-Pous, Helena |
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. |
Keywords: | detection machine learning phishing phishing URL |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | 2-Jun-2020 |
Publication license: | http://creativecommons.org/licenses/by-nc-sa/3.0/es/ |
Appears in Collections: | Bachelor thesis, research projects, etc. |
Files in This Item:
File | Description | Size | Format | |
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bmarin01TFM062memoria.pdf | Memoria del TFM | 911,6 kB | Adobe PDF | View/Open |
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