Federated Learning to detect malicious network traffic in IoT environments

Federated Learning allows training machine learning models with decentralized data while preserving its privacy by design. Thus, it appears as an ideal solution to detect attacks to IoT devices without the need of revealing sensitive information.

Detalles Bibliográficos
Autor: Vallejo I Benito, Roger
Tipo de recurso: tesis de maestría
Fecha de publicación:2023
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/403284
Acceso en línea:https://hdl.handle.net/2117/403284
Access Level:acceso abierto
Palabra clave:Computer security
Internet of things
Federated Learning
IoT
Cybersecurity
Seguretat informàtica
Internet de les coses
Àrees temàtiques de la UPC::Informàtica::Seguretat informàtica
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spelling Federated Learning to detect malicious network traffic in IoT environmentsVallejo I Benito, RogerComputer securityInternet of thingsFederated LearningIoTCybersecuritySeguretat informàticaInternet de les cosesÀrees temàtiques de la UPC::Informàtica::Seguretat informàticaFederated Learning allows training machine learning models with decentralized data while preserving its privacy by design. Thus, it appears as an ideal solution to detect attacks to IoT devices without the need of revealing sensitive information.This thesis consists in the development and analysis of Federated Learning to detect malicious network traffic in IoT environments. The motivation of the project is based on two main aspects, the poor security measures in the actual IoT devices and the necessity of preserving data privacy in Machine Learning processes. First, this project goes through an overview of Machine Learning concepts, followed by explanations of the most common attacks to IoT devices. We will also find information about Federated Learning and its main characteristics. Second, we can find two practical parts. The first one consists in applying Centralised Learning to the chosen dataset and with 3 different algorithms. After that, the entire dataset has been divided into several smaller ones representing different IoT devices in a network, and the same three algorithms have been applied following two different Federated Learning strategies.Universitat Politècnica de CatalunyaLeón Abarca, Olga20232023-07-1720242024-02-27master thesishttp://purl.org/coar/resource_type/c_bdccNAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/2117/403284reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4032842026-05-27T15:37:01Z
dc.title.none.fl_str_mv Federated Learning to detect malicious network traffic in IoT environments
title Federated Learning to detect malicious network traffic in IoT environments
spellingShingle Federated Learning to detect malicious network traffic in IoT environments
Vallejo I Benito, Roger
Computer security
Internet of things
Federated Learning
IoT
Cybersecurity
Seguretat informàtica
Internet de les coses
Àrees temàtiques de la UPC::Informàtica::Seguretat informàtica
title_short Federated Learning to detect malicious network traffic in IoT environments
title_full Federated Learning to detect malicious network traffic in IoT environments
title_fullStr Federated Learning to detect malicious network traffic in IoT environments
title_full_unstemmed Federated Learning to detect malicious network traffic in IoT environments
title_sort Federated Learning to detect malicious network traffic in IoT environments
dc.creator.none.fl_str_mv Vallejo I Benito, Roger
author Vallejo I Benito, Roger
author_facet Vallejo I Benito, Roger
author_role author
dc.contributor.none.fl_str_mv León Abarca, Olga
dc.subject.none.fl_str_mv Computer security
Internet of things
Federated Learning
IoT
Cybersecurity
Seguretat informàtica
Internet de les coses
Àrees temàtiques de la UPC::Informàtica::Seguretat informàtica
topic Computer security
Internet of things
Federated Learning
IoT
Cybersecurity
Seguretat informàtica
Internet de les coses
Àrees temàtiques de la UPC::Informàtica::Seguretat informàtica
description Federated Learning allows training machine learning models with decentralized data while preserving its privacy by design. Thus, it appears as an ideal solution to detect attacks to IoT devices without the need of revealing sensitive information.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-07-17
2024
2024-02-27
dc.type.none.fl_str_mv master thesis
http://purl.org/coar/resource_type/c_bdcc
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/403284
url https://hdl.handle.net/2117/403284
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universitat Politècnica de Catalunya
publisher.none.fl_str_mv Universitat Politècnica de Catalunya
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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