loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Mohammed Al-Obeidallah 1 ; Luca Piras 2 ; Onyinye Iloanugo 3 ; Haralambos Mouratidis 4 ; Duaa Alkubaisy 5 and Daniele Dellagiacoma 6

Affiliations: 1 Department of Software Engineering, Al Ain University, Abu Dhabi, U.A.E. ; 2 School of Computing, Middlesex University, London, U. K. ; 3 School of Computing, Robert Gordon University, Aberdeen, U. K. ; 4 Institute for Analytics and Data Science, University of Essex, Colchester, U. K. ; 5 College of Applied Studies and Community Service, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia ; 6 Centre for Secure, Intelligent and Usable Systems, University of Brighton, Brighton, U. K.

Keyword(s): Requirements Modeling, Requirements Engineering, Privacy-by-Design, Goal Modeling, GDPR, Design Patterns.

Abstract: The introduction of the European General Data Protection Regulation (GDPR) has imposed obligations on organisations collecting data in the EU. This has been beneficial to citizens due to rights reinforcement achieved as data subjects. However, obligations heavily affected organisations, and their privacy requirements analysts, having issues with interpreting and implementing GDPR principles. This paper proposes visual GDPR Patterns supporting analysts through Privacy-by- Design (PbD) and GDPR compliance analysis. In order to achieve that, we extended a requirements modeling tool, SecTro, which is used to assist analysts in creating visual requirements models. Specifically, we extended SecTro with novel visual GDPR patterns representing GDPR principles. We evaluated the patterns in a healthcare case study. The evaluation results suggest that the GDPR patterns can help analysts in PbD modeling analysis, by representing GDPR principles and considering relevant ready-to-use alternatives, towards achieving GDPR compliance. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.15.145.50

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Al-Obeidallah, M.; Piras, L.; Iloanugo, O.; Mouratidis, H.; Alkubaisy, D. and Dellagiacoma, D. (2023). Goal-Modeling Privacy-by-Design Patterns for Supporting GDPR Compliance. In Proceedings of the 18th International Conference on Software Technologies - ICSOFT; ISBN 978-989-758-665-1; ISSN 2184-2833, SciTePress, pages 361-368. DOI: 10.5220/0012080700003538

@conference{icsoft23,
author={Mohammed Al{-}Obeidallah. and Luca Piras. and Onyinye Iloanugo. and Haralambos Mouratidis. and Duaa Alkubaisy. and Daniele Dellagiacoma.},
title={Goal-Modeling Privacy-by-Design Patterns for Supporting GDPR Compliance},
booktitle={Proceedings of the 18th International Conference on Software Technologies - ICSOFT},
year={2023},
pages={361-368},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012080700003538},
isbn={978-989-758-665-1},
issn={2184-2833},
}

TY - CONF

JO - Proceedings of the 18th International Conference on Software Technologies - ICSOFT
TI - Goal-Modeling Privacy-by-Design Patterns for Supporting GDPR Compliance
SN - 978-989-758-665-1
IS - 2184-2833
AU - Al-Obeidallah, M.
AU - Piras, L.
AU - Iloanugo, O.
AU - Mouratidis, H.
AU - Alkubaisy, D.
AU - Dellagiacoma, D.
PY - 2023
SP - 361
EP - 368
DO - 10.5220/0012080700003538
PB - SciTePress