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ETDs @PUC-Rio
Estatística
Título: ENABLING DATA REGULATION EVALUATION THROUGH INTELLIGENT AND NORMATIVE MULTIAGENT SYSTEMS DESIGN
Autor: PAULO HENRIQUE CARDOSO ALVES
Colaborador(es): HELIO CORTES VIEIRA LOPES - Orientador
CLARISSE SIECKENIUS DE SOUZA - Coorientador
Catalogação: 28/NOV/2023 Língua(s): ENGLISH - UNITED STATES
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=65178&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=65178&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.65178
Resumo:
Sharing and managing personal data are challenging due to the massive amount of data generated, uploaded, and digitalized, informed by data subjects to utilize services, online or not. This challenge disrespects not only the data subjects, but also data controllers and processors, which are responsible for security, privacy, anonymity, and data usage under the legal basis applied and the initial purpose when the data were required. In this scenario, data protection and regulation take place to organize this environment proposing rights and duties to the involved agents. However, each country is free to create and employ its data regulation, e.g., GDPR in European Union and LGPD in Brazil. Therefore, although the goal is to protect the data subjects, the regulations can present different rules based on their jurisdiction. In this scenario, ontologies emerge to identify the entities and relationships to show them at a high abstraction level, facilitating ontology alignment with different regulations. To do so, we developed a metamodel based on GDPR ontologies to enable the LGPD representation focused on the consent legal basis. Moreover, we proposed GoDReP (Generation of Data Regulation Plots) to allow actors to represent their law s interpretation in a specific application scenario. As a result, we set three scenarios to exercise the GoDReP application. Moreover, in this thesis, we also propose an intelligent normative multiagent system architecture (RegulAI) to represent the personal data regulation rights and obligations, as well as the agent s decision-making process. Finally, we developed a use case applying RegulAI in the open banking scenario.
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