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Title: | Entrenament d'un arbre de decisió per a la detecció d'atacs distribuïts de denegació de servei (DDoS). Una aproximació |
Author: | Farràs Ballabriga, Gerard |
Director: | Rifà-Pous, Helena |
Tutor: | Hernández Jiménez, Enric |
Abstract: | In the information and knowledge society of the 21st century, the information of each organization is highly valuable. The possibility of uninterrupted and secure use of information systems becomes an essential task for public and private organizations around the world. Within this context, the operational continuity of all information systems must be guaranteed. Distributed denial of service attacks (DDoS) are attacks that, using multiple techniques, impair the continued use of information systems. It is necessary, therefore, to find tools that mitigate these types of attacks. There are currently software-based mechanisms that ensure information systems, but work must be done to implement them with low-cost computational techniques and also ensure that they are updated day by day. A field currently in search and with a lot of future projection involves using artificial intelligence and machine learning techniques for real-time detection of what an attack could be. In this work, an implementation of a decision tree is carried out using machine learning techniques on a set of network traffic data (dataset) with DDoS attacks. |
Keywords: | cyber security dataset machine learning decision trees DDoS |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | 29-Dec-2019 |
Publication license: | http://creativecommons.org/licenses/by/3.0/es/ |
Appears in Collections: | Trabajos finales de carrera, trabajos de investigación, etc. |
Files in This Item:
File | Description | Size | Format | |
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gfarrasbTFM1219.pdf | Memòria del TFM | 1,13 MB | Adobe PDF | View/Open |
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