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Autores
Orientador(es)
Resumo(s)
This study focuses on enhancing the BITalino ecosystem, a platform for acquiring biometric signals through sensor based devices. Until now, the processing of these biosignals relied on standalone scripts without a supporting infrastructure. To address these issues, we developed a Kubernetes-based architecture using microservices to enable containerized script execution. For storing the resulting output files, we implemented an object storage solution suitable for handling unstructured data. The handling of biometric data also introduces regulatory challenges in this virtualization. Since such data is considered sensitive under the General Data Protection Regulation (GDPR), the system incorporates mechanisms for anonymization or full deletion of data, ensuring the privacy of the users. Measures were implemented to mitigate the OWASP Top 10 vulnerabilities, enhancing the overall security and reliability of the system. As a case study, the solution was validated in the context of swimming, where scripts for processing session files were executed through APIs, with some adaptations, Kubernetes Jobs and CronJobs.
Descrição
Tese de Mestrado, Engenharia Informática, 2026, Universidade de Lisboa, Faculdade de Ciências
Palavras-chave
Virtualization Infrastructure Privacy BITalino Security
