Large-scale web tracking and cookie compliance: Evaluating one million websites under GDPR with AI categorization

With the increasing prevalence of web-tracking technologies, including tracking cookies, pixel tracking, and browser fingerprinting techniques, there is a pressing need to analyze their impact on user privacy. Despite the growing interest in the scholarly literature, large-scale, fully automatic eva...

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Detalles Bibliográficos
Autores: Martínez Álvarez, David, Molero Grau, Aniol, Calle Ortega, Eusebi, Canals Ametller, Dolors, Jové, Albert
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/26902
Acceso en línea:http://hdl.handle.net/10256/26902
Access Level:acceso abierto
Palabra clave:Protecció de dades
Intel·ligència artificial
Data protection
Artificial intelligence
Internet -- Mesures de seguretat
Internet -- Security measures
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spelling Large-scale web tracking and cookie compliance: Evaluating one million websites under GDPR with AI categorizationMartínez Álvarez, DavidMolero Grau, AniolCalle Ortega, EusebiCanals Ametller, DolorsJové, AlbertProtecció de dadesIntel·ligència artificialData protectionArtificial intelligenceInternet -- Mesures de seguretatInternet -- Security measuresWith the increasing prevalence of web-tracking technologies, including tracking cookies, pixel tracking, and browser fingerprinting techniques, there is a pressing need to analyze their impact on user privacy. Despite the growing interest in the scholarly literature, large-scale, fully automatic evaluations of website compliance with privacy regulations remain scarce. In this paper, we present new algorithms, methods, and an AI categorization model designed for massive, fully automatic analyses of web-tracking and cookie compliance and usage with and without valid user consent. Utilizing the recently published Website Evidence Collector (WEC) software from the European Data Protection Supervisor (EDPS), these algorithms are applied to assess over one million websites from Tranco's top list under European GDPR regulation. A novel 22-category multilabel AI model for website categorization provides content-based context to compliance results, achieving 96.56% accuracy and an F1 score of 0.963. Results reveal that nearly half of the websites utilize tracking cookies, while over half employ pixel tracking without user consent, thus highlighting significant differences between websites' content categories. Additionally, our analysis demonstrates how web-tracking power is concentrated among just a few companies, with the top 10 tracking firms being responsible for most compliance violations related to obtaining valid user consent. This paper serves as a foundation for ongoing large-scale web-tracking analyses, essential for understanding trends over time and evaluating the effectiveness of privacy regulationsThe University of Girona Institute of Informatics and Applications researchers thank the Generalitat de Catalunya for their support through a Consolidated Research Group (2021 SGR 01125). David Martínez thanks the University of Girona for his FI fellowship (IFUdG 46 2022)Open Access funding provided thanks to the CRUE-CSIC agreement with ElsevierElsevier2025info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionpeer-reviewedapplication/pdfhttp://hdl.handle.net/10256/26902http://hdl.handle.net/10256/26902Journal of Network and Computer Applications, 2025, vol. 242, núm. art.núm.104222Articles publicats (D-ATC)Martínez Álvarez, David Molero Grau, Aniol Calle Ortega, Eusebi Canals Ametller, Dolors Jové, Albert 2025 Large-scale web tracking and cookie compliance: Evaluating one million websites under GDPR with AI categorization Journal of Network and Computer Applications 242 art.núm.104222reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.jnca.2025.104222info:eu-repo/semantics/altIdentifier/issn/1084-8045Reconeixement 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessoai:recercat.cat:10256/269022026-05-29T05:05:01Z
dc.title.none.fl_str_mv Large-scale web tracking and cookie compliance: Evaluating one million websites under GDPR with AI categorization
title Large-scale web tracking and cookie compliance: Evaluating one million websites under GDPR with AI categorization
spellingShingle Large-scale web tracking and cookie compliance: Evaluating one million websites under GDPR with AI categorization
Martínez Álvarez, David
Protecció de dades
Intel·ligència artificial
Data protection
Artificial intelligence
Internet -- Mesures de seguretat
Internet -- Security measures
title_short Large-scale web tracking and cookie compliance: Evaluating one million websites under GDPR with AI categorization
title_full Large-scale web tracking and cookie compliance: Evaluating one million websites under GDPR with AI categorization
title_fullStr Large-scale web tracking and cookie compliance: Evaluating one million websites under GDPR with AI categorization
title_full_unstemmed Large-scale web tracking and cookie compliance: Evaluating one million websites under GDPR with AI categorization
title_sort Large-scale web tracking and cookie compliance: Evaluating one million websites under GDPR with AI categorization
dc.creator.none.fl_str_mv Martínez Álvarez, David
Molero Grau, Aniol
Calle Ortega, Eusebi
Canals Ametller, Dolors
Jové, Albert
author Martínez Álvarez, David
author_facet Martínez Álvarez, David
Molero Grau, Aniol
Calle Ortega, Eusebi
Canals Ametller, Dolors
Jové, Albert
author_role author
author2 Molero Grau, Aniol
Calle Ortega, Eusebi
Canals Ametller, Dolors
Jové, Albert
author2_role author
author
author
author
dc.subject.none.fl_str_mv Protecció de dades
Intel·ligència artificial
Data protection
Artificial intelligence
Internet -- Mesures de seguretat
Internet -- Security measures
topic Protecció de dades
Intel·ligència artificial
Data protection
Artificial intelligence
Internet -- Mesures de seguretat
Internet -- Security measures
description With the increasing prevalence of web-tracking technologies, including tracking cookies, pixel tracking, and browser fingerprinting techniques, there is a pressing need to analyze their impact on user privacy. Despite the growing interest in the scholarly literature, large-scale, fully automatic evaluations of website compliance with privacy regulations remain scarce. In this paper, we present new algorithms, methods, and an AI categorization model designed for massive, fully automatic analyses of web-tracking and cookie compliance and usage with and without valid user consent. Utilizing the recently published Website Evidence Collector (WEC) software from the European Data Protection Supervisor (EDPS), these algorithms are applied to assess over one million websites from Tranco's top list under European GDPR regulation. A novel 22-category multilabel AI model for website categorization provides content-based context to compliance results, achieving 96.56% accuracy and an F1 score of 0.963. Results reveal that nearly half of the websites utilize tracking cookies, while over half employ pixel tracking without user consent, thus highlighting significant differences between websites' content categories. Additionally, our analysis demonstrates how web-tracking power is concentrated among just a few companies, with the top 10 tracking firms being responsible for most compliance violations related to obtaining valid user consent. This paper serves as a foundation for ongoing large-scale web-tracking analyses, essential for understanding trends over time and evaluating the effectiveness of privacy regulations
publishDate 2025
dc.date.none.fl_str_mv 2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
peer-reviewed
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10256/26902
http://hdl.handle.net/10256/26902
url http://hdl.handle.net/10256/26902
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jnca.2025.104222
info:eu-repo/semantics/altIdentifier/issn/1084-8045
dc.rights.none.fl_str_mv Reconeixement 4.0 Internacional
http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Reconeixement 4.0 Internacional
http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv Journal of Network and Computer Applications, 2025, vol. 242, núm. art.núm.104222
Articles publicats (D-ATC)
Martínez Álvarez, David Molero Grau, Aniol Calle Ortega, Eusebi Canals Ametller, Dolors Jové, Albert 2025 Large-scale web tracking and cookie compliance: Evaluating one million websites under GDPR with AI categorization Journal of Network and Computer Applications 242 art.núm.104222
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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