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http://hdl.handle.net/10609/118166
Title: | Aplicación de técnicas de machine learning a la ciberseguridad: Aprendizaje supervisado para la detección de amenazas web mediante clasificación basada en árboles de decisión |
Author: | Dueñas Quesada, José María |
Director: | Rifà-Pous, Helena |
Tutor: | Hernández Jiménez, Enric |
Abstract: | The purpose of this Master thesis is to develop a decision tree based predictive machine learning model which main task is to classify a set of HTTP requests in normal and anomalous ones. The thesis includes a state-of-the-art survey on the main applications of the machine learning in the cybersecurity field, the implementation of the proposed decision tree classifier model with the Python language and the Scikit-learn library and the analysis of the results obtained on the application of the implemented model against the CSIC-2010 dataset. The proposed model in this thesis achieved a 100% of accuracy in classifying the HTTP requests. |
Keywords: | decision trees machine learning computer security cybersecurity data analysis supervised learning |
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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joseduenasTFM0620memoria.pdf | 3,54 MB | Adobe PDF | View/Open |
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