Privacytracker: A privacy-by-design GDPR-compliant framework with verifiable data traceability controls

Harald Gjermundrød; Ioanna Dionysiou; Kyriakos Costa

doi:10.1007/978-3-319-46963-8_1

Privacytracker: A privacy-by-design GDPR-compliant framework with verifiable data traceability controls

Harald Gjermundrød, Ioanna Dionysiou, Kyriakos Costa

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Breach or lack of online privacy has become almost a commonplace of today’s digital age, mainly due to the inability of either enforcing privacy requirements or imposing strict sanctions against violations. The current state of affairs in data privacy is at a turning point for companies operating in EU state members as the enforcement of the General Data Protection Regulation (GDPR) empowers users with control over their personal data, including regulating its disclosure, withdrawing disclosure consent at any given time and tracking their data trail. Compliance with the GDPR is mandatory and it requires signifiant amendments and/or restructuring of data processing routines undertaken by enterprises. Currently, there is no framework to support the GDPR principles. This paper proposes privacyTracker, a GDPR-compliant framework that supports basic GDPR principles including data traceability and allowing a user to get a cryptographically verifiable snapshot of his/her data trail.

Original language	English
Title of host publication	Current Trends in Web Engineering - ICWE 2016 International Workshops DUI, TELERISE, SoWeMine, and Liquid Web, Revised Selected Papers
Publisher	Springer Verlag
Pages	3-15
Number of pages	13
Volume	9881 LNCS
ISBN (Print)	9783319469621
DOIs	https://doi.org/10.1007/978-3-319-46963-8_1
Publication status	Published - 2016
Event	International Conference on Web Engineering, ICWE 2016 and 2nd International Workshop on TEchnical and LEgal aspects of data pRIvacy and SEcurity, TELERISE 2016, 2nd International Workshop on Mining the Social Web, SoWeMine 2016, 1st International Workshop on Liquid Multi-Device Software for the Web, LiquidWS 2016, 5th Workshop on Distributed User Interfaces: Distributing Interactions, DUI 2016 - Lugano, Switzerland Duration: 6 Jun 2016 → 9 Jun 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9881 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	International Conference on Web Engineering, ICWE 2016 and 2nd International Workshop on TEchnical and LEgal aspects of data pRIvacy and SEcurity, TELERISE 2016, 2nd International Workshop on Mining the Social Web, SoWeMine 2016, 1st International Workshop on Liquid Multi-Device Software for the Web, LiquidWS 2016, 5th Workshop on Distributed User Interfaces: Distributing Interactions, DUI 2016
Country/Territory	Switzerland
City	Lugano
Period	6/06/16 → 9/06/16

Keywords

Data traceability
General Data Protection Regulation (GDPR)
User privacy

Access to Document

10.1007/978-3-319-46963-8_1

Cite this

Gjermundrød, H., Dionysiou, I., & Costa, K. (2016). Privacytracker: A privacy-by-design GDPR-compliant framework with verifiable data traceability controls. In Current Trends in Web Engineering - ICWE 2016 International Workshops DUI, TELERISE, SoWeMine, and Liquid Web, Revised Selected Papers (Vol. 9881 LNCS, pp. 3-15). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9881 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46963-8_1

Gjermundrød, Harald ; Dionysiou, Ioanna ; Costa, Kyriakos. / Privacytracker : A privacy-by-design GDPR-compliant framework with verifiable data traceability controls. Current Trends in Web Engineering - ICWE 2016 International Workshops DUI, TELERISE, SoWeMine, and Liquid Web, Revised Selected Papers. Vol. 9881 LNCS Springer Verlag, 2016. pp. 3-15 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Breach or lack of online privacy has become almost a commonplace of today{\textquoteright}s digital age, mainly due to the inability of either enforcing privacy requirements or imposing strict sanctions against violations. The current state of affairs in data privacy is at a turning point for companies operating in EU state members as the enforcement of the General Data Protection Regulation (GDPR) empowers users with control over their personal data, including regulating its disclosure, withdrawing disclosure consent at any given time and tracking their data trail. Compliance with the GDPR is mandatory and it requires signifiant amendments and/or restructuring of data processing routines undertaken by enterprises. Currently, there is no framework to support the GDPR principles. This paper proposes privacyTracker, a GDPR-compliant framework that supports basic GDPR principles including data traceability and allowing a user to get a cryptographically verifiable snapshot of his/her data trail.",

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Gjermundrød, H , Dionysiou, I & Costa, K 2016, Privacytracker: A privacy-by-design GDPR-compliant framework with verifiable data traceability controls. in Current Trends in Web Engineering - ICWE 2016 International Workshops DUI, TELERISE, SoWeMine, and Liquid Web, Revised Selected Papers. vol. 9881 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9881 LNCS, Springer Verlag, pp. 3-15, International Conference on Web Engineering, ICWE 2016 and 2nd International Workshop on TEchnical and LEgal aspects of data pRIvacy and SEcurity, TELERISE 2016, 2nd International Workshop on Mining the Social Web, SoWeMine 2016, 1st International Workshop on Liquid Multi-Device Software for the Web, LiquidWS 2016, 5th Workshop on Distributed User Interfaces: Distributing Interactions, DUI 2016, Lugano, Switzerland, 6/06/16. https://doi.org/10.1007/978-3-319-46963-8_1

Privacytracker: A privacy-by-design GDPR-compliant framework with verifiable data traceability controls. / Gjermundrød, Harald ; Dionysiou, Ioanna; Costa, Kyriakos.
Current Trends in Web Engineering - ICWE 2016 International Workshops DUI, TELERISE, SoWeMine, and Liquid Web, Revised Selected Papers. Vol. 9881 LNCS Springer Verlag, 2016. p. 3-15 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9881 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Breach or lack of online privacy has become almost a commonplace of today’s digital age, mainly due to the inability of either enforcing privacy requirements or imposing strict sanctions against violations. The current state of affairs in data privacy is at a turning point for companies operating in EU state members as the enforcement of the General Data Protection Regulation (GDPR) empowers users with control over their personal data, including regulating its disclosure, withdrawing disclosure consent at any given time and tracking their data trail. Compliance with the GDPR is mandatory and it requires signifiant amendments and/or restructuring of data processing routines undertaken by enterprises. Currently, there is no framework to support the GDPR principles. This paper proposes privacyTracker, a GDPR-compliant framework that supports basic GDPR principles including data traceability and allowing a user to get a cryptographically verifiable snapshot of his/her data trail.

KW - Data traceability

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Gjermundrød H , Dionysiou I, Costa K. Privacytracker: A privacy-by-design GDPR-compliant framework with verifiable data traceability controls. In Current Trends in Web Engineering - ICWE 2016 International Workshops DUI, TELERISE, SoWeMine, and Liquid Web, Revised Selected Papers. Vol. 9881 LNCS. Springer Verlag. 2016. p. 3-15. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46963-8_1

Privacytracker: A privacy-by-design GDPR-compliant framework with verifiable data traceability controls

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