Article (Scientific journals)
Qualifying and Measuring Transparency: A Medical Data System Case Study
Spagnuelo, Dayana; Bartolini, Cesare; Lenzini, Gabriele
2020In Computers and Security
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Abstract :
[en] Transparency is a data processing principle enforced by the GDPR but purposely left open to interpretation. As such, the means to adhere to it are left unspecified. Article 29 Working Party provides practical guidance on how to interpret transparency, however there are no defined requirements nor ways to verify the quality of the implementation of transparency. We address this problem. We discuss and define applicable metrics for transparency, propose how measurement can be conducted in an operative system, and suggest a practical way in which these metrics can be interpreted in order to increase confidence that transparency is realised in a system.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Spagnuelo, Dayana;  Vrije Universiteit Amsterdam - VU > Faculty of Science, Business Web and Media > Lecturer
Bartolini, Cesare ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Lenzini, Gabriele ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
External co-authors :
yes
Language :
English
Title :
Qualifying and Measuring Transparency: A Medical Data System Case Study
Publication date :
2020
Journal title :
Computers and Security
ISSN :
0167-4048
Publisher :
Elsevier, United Kingdom
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Security, Reliability and Trust
FnR Project :
FNR11333956 - Data Protection Regulation Compliance, 2016 (01/02/2017-30/06/2019) - Gabriele Lenzini
Available on ORBilu :
since 23 January 2020

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