Blar i UiS Brage på forfatter "Wibawa, Febrianti"

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    • BFV-Based Homomorphic Encryption for Privacy-Preserving CNN Models 

      Wibawa, Febrianti; Catak, Ferhat Özgur; Sarp, Salih; Kuzlu, Murat (Peer reviewed; Journal article, 2022)
      Medical data is frequently quite sensitive in terms of data privacy and security. Federated learning has been used to increase the privacy and security of medical data, which is a sort of machine learning technique. The ...

    • Privacy-Preserving Machine Learning for Health Institutes 

      Wibawa, Febrianti (Master thesis, 2022)
      Medical data is, due to its nature, often susceptible to data privacy and security concerns. The identity of a person can be derived from medical data. Federated learning, one type of machine learning technique, is popularly ...