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Challenges in the Implementation of Privacy Enhancing Semantic Technologies (PESTs) Supporting GDPR

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AI Approaches to the Complexity of Legal Systems XI-XII (AICOL 2020, AICOL 2018, XAILA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13048))

Abstract

The EU General Data Protection Regulation (GDPR) imposes different requirements for data controllers collecting personal data to protect individuals’ privacy. This fact triggered many studies and projects to investigate Privacy Enhancing Technologies (PETs) for the fulfillment of the compliance requirements. In this paper, after reviewing some of the current challenges and gaps in GDPR compliance, we argue the use of Semantic Technologies in PETs in the form of an Intelligent Compliance Agent (ICA) to support data controllers in carrying out a Data Protection Impact Assessment (DPIA). Models and ontologies representing entities involved in the DPIA process can help data controllers determine the risk of their processing activities. Additionally, an inference engine, equipped with a knowledge base of DPIA-related obligations, can effectively assist data controllers in taking specific actions when a legal fact is triggered based on met conditions.

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Notes

  1. 1.

    https://eur-lex.europa.eu/eli/reg/2016/679/oj.

  2. 2.

    https://dpvcg.github.io/dpv/.

  3. 3.

    https://www.w3.org/TR/shacl/.

  4. 4.

    Business Process Re-engineering and functional toolkit for GDPR compliance.

  5. 5.

    https://ai.wu.ac.at/policies/policylanguage/#basic-usage-policies.

  6. 6.

    https://ai.wu.ac.at/policies/policylog/.

  7. 7.

    https://www.mirelproject.eu/.

  8. 8.

    https://github.com/dapreco/daprecokb.

  9. 9.

    https://www.w3.org/Submission/SWRL/.

  10. 10.

    https://www.w3.org/2005/rules/wg/charter.html.

  11. 11.

    http://www.estrellaproject.org/lkif-core/.

  12. 12.

    http://www.ruleml.org/.

  13. 13.

    https://www.w3.org/TR/odrl-vocab/.

  14. 14.

    https://www.cnil.fr/en/privacy-impact-assessment-pia.

  15. 15.

    https://ec.europa.eu/commission/presscorner/detail/en/ip_21_1682.

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Acknowledgements

This research has been supported by European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813497 (PROTECT).

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Authors and Affiliations

  1. Ontology Engineering Group, Universidad Politécnica de Madrid, Madrid, Spain

    Rana Saniei

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  1. Rana Saniei
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Correspondence to Rana Saniei .

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Editors and Affiliations

  1. Technical University of Madrid, Madrid, Spain

    Víctor Rodríguez-Doncel

  2. University of Bologna, Bologna, Italy

    Monica Palmirani

  3. Jagiellonian University, Krakow, Poland

    Michał Araszkiewicz

  4. La Trobe University, Melbourne, VIC, Australia

    Pompeu Casanovas

  5. University of Turin, Turin, Italy

    Ugo Pagallo

  6. University of Bologna, Bologna, Italy

    Giovanni Sartor

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Saniei, R. (2021). Challenges in the Implementation of Privacy Enhancing Semantic Technologies (PESTs) Supporting GDPR. In: Rodríguez-Doncel, V., Palmirani, M., Araszkiewicz, M., Casanovas, P., Pagallo, U., Sartor, G. (eds) AI Approaches to the Complexity of Legal Systems XI-XII. AICOL AICOL XAILA 2020 2018 2020. Lecture Notes in Computer Science(), vol 13048. Springer, Cham. https://doi.org/10.1007/978-3-030-89811-3_20

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