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The Future of International Data Transfers: Managing Legal Risk with a User-Held Data Model
by
Marcelo Corrales Compagnucci
, Jurcys, Paulius
, Fenwick, Mark
in
Cloud computing
/ Data models
/ Personal information
/ Prohibition
/ Risk management
2024
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Do you wish to request the book?
The Future of International Data Transfers: Managing Legal Risk with a User-Held Data Model
by
Marcelo Corrales Compagnucci
, Jurcys, Paulius
, Fenwick, Mark
in
Cloud computing
/ Data models
/ Personal information
/ Prohibition
/ Risk management
2024
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The Future of International Data Transfers: Managing Legal Risk with a User-Held Data Model
Paper
The Future of International Data Transfers: Managing Legal Risk with a User-Held Data Model
2024
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Overview
The General Data Protection Regulation contains a blanket prohibition on the transfer of personal data outside of the European Economic Area unless strict requirements are met. The rationale for this provision is to protect personal data and data subject rights by restricting data transfers to countries that may not have the same level of protection as the EEA. However, the ubiquitous and permeable character of new technologies such as cloud computing, and the increased inter connectivity between societies, has made international data transfers the norm and not the exception. The Schrems II case and subsequent regulatory developments have further raised the bar for companies to comply with complex and, often, opaque rules. Many firms are, therefore, pursuing technology-based solutions in order to mitigate this new legal risk. These emerging technological alternatives reduce the need for open-ended cross-border transfers and the practical challenges and legal risk that such transfers create after Schrems. This article examines one such alternative, namely a user-held data model. This approach takes advantage of personal data clouds that allows data subjects to store their data locally and in a more decentralised manner, thus decreasing the need for cross-border transfers and offering end-users the possibility of greater control over their data.
Publisher
Cornell University Library, arXiv.org
Subject
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