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Search: id:"swepub:oai:research.chalmers.se:5b550358-494a-493c-b1b8-ac315040fc15" > Towards a GDPR-comp...

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  • Cambronero, Maria Emilia,1978Universidad de Castilla, La Mancha,University of Castilla, La Mancha (author)

Towards a GDPR-compliant cloud architecture with data privacy controlled through sticky policies

  • Article/chapterEnglish2024

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  • 2024
  • electronicrdacarrier

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  • LIBRIS-ID:oai:research.chalmers.se:5b550358-494a-493c-b1b8-ac315040fc15
  • https://doi.org/10.7717/peerj-cs.1898DOI
  • https://research.chalmers.se/publication/540542URI

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  • Language:English
  • Summary in:English

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  • Subject category:art swepub-publicationtype
  • Subject category:ref swepub-contenttype

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  • Data privacy is one of the biggest challenges facing system architects at the system design stage. Especially when certain laws, such as the General Data Protection Regulation (GDPR), have to be complied with by cloud environments. In this article, we want to help cloud providers comply with the GDPR by proposing a GDPR-compliant cloud architecture. To do this, we use model-driven engineering techniques to design cloud architecture and analyze cloud interactions. In particular, we develop a complete framework, called MDCT, which includes a Unified Modeling Language profile that allows us to define specific cloud scenarios and profile validation to ensure that certain required properties are met. The validation process is implemented through the Object Constraint Language (OCL) rules, which allow us to describe the constraints in these models. To comply with many GDPR articles, the proposed cloud architecture considers data privacy and data tracking, enabling safe and secure data management and tracking in the context of the cloud. For this purpose, sticky policies associated with the data are incorporated to define permission for third parties to access the data and track instances of data access. As a result, a cloud architecture designed with MDCT contains a set of OCL rules to validate it as a GDPR-compliant cloud architecture. Our tool models key GDPR points such as user consent/withdrawal, the purpose of access, and data transparency and auditing, and considers data privacy and data tracking with the help of sticky policies.

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  • Martínez-Pietro, Miguel A.Universidad de Castilla, La Mancha,University of Castilla, La Mancha (author)
  • Llana Diaz, Luis FernandoUniversidad Complutense de Madrid,Complutense University (author)
  • Rodriguez, Ricardo J.Universidad de Zaragoza,University of Zaragoza (author)
  • Russo, Alejandro,1978Chalmers tekniska högskola,Chalmers University of Technology(Swepub:cth)russo (author)
  • Universidad de Castilla, La ManchaUniversidad Complutense de Madrid (creator_code:org_t)

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  • In:PeerJ Computer Science10

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