Security And Privacy Of Medical Data: Challenges For Next-Generation Patient-Centric Healthcare Systems

Vladimir Janjic, Juliana Bowles, Marios Belk, Andreas Pitsillides

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

We describe the recently-started EU H2020 Serums: Securing Medical Data in Smart Patient-Centric Healthcare Systems project that aims to develop novel techniques for safe and secure collection, storage, exchange and analysis of medical data, allowing the patients of the next-generation smart healthcare centers to get the best possible treatment while respecting privacy and ownership of their sensitive personal data. Our goal is to significantly enhance trust in the new medical systems. We outline the techniques that will be extended/developed over the course of the project and describe the use cases that will be used to verify the effectiveness of these technologies in practice.

Original languageEnglish
Title of host publicationACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization
Place of PublicationNew York
PublisherAssociation for Computing Machinery
Pages213-214
Number of pages2
ISBN (Electronic)9781450367110
DOIs
Publication statusPublished - 9 Jun 2019
Event27th ACM International Conference on User Modeling, Adaptation and Personalization, UMAP 2019 - Larnaca, Cyprus
Duration: 9 Jun 201912 Jun 2019

Conference

Conference27th ACM International Conference on User Modeling, Adaptation and Personalization, UMAP 2019
CountryCyprus
CityLarnaca
Period9/06/1912/06/19

Keywords

  • Data Sharing
  • Medical data
  • Personalised Medicine
  • Privacy
  • Security
  • Smart Healthcare

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  • Cite this

    Janjic, V., Bowles, J., Belk, M., & Pitsillides, A. (2019). Security And Privacy Of Medical Data: Challenges For Next-Generation Patient-Centric Healthcare Systems. In ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization (pp. 213-214). Association for Computing Machinery. https://doi.org/10.1145/3314183.3326364