Towards Automated GDPR Compliance Checking

Libal, Tomer

doi:10.1007/978-3-030-73959-1_1

Cited by 5 publications

(2 citation statements)

References 19 publications

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“…Their work focuses on accurately encoding the law, but it does support enforcement. Smaller fragments of the GDPR have been represented in other formalisms providing some support for automated reasoning, such as deontic logic [1,31], LegalRuleML [33], OCL [44], OWL2 [11], and Prolog [16]. In a different line of research, several policy languages were designed explicitly with GDPR provisions in mind [3,20,41,47,48 GDPR compliance by design.…”

Section: Discussionmentioning

confidence: 99%

Enforcing the GDPR

Hublet,

Basin,

Krstić

2024

Lecture Notes in Computer Science

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Violations of data protection laws such as the General Data Protection Regulation (GDPR) are ubiquitous. Currently building IT support to implement such laws is difficult and the alternatives such as manual controls augmented by auditing are limited and scale poorly. This calls for new automated enforcement techniques that can build on, and enforce, a formalization of the law. In this paper, we present the first enforceable specification of a core set of GDPR provisions, centered on data-subject rights, and describe an architecture that automatically enforces this specification in web applications. We evaluate our architecture by implementing three case studies and show that our approach incurs only modest development and runtime overhead, while covering the most relevant privacy-related aspects of GDPR that can be enforced at runtime.

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Section: Discussionmentioning

confidence: 99%

Enforcing the GDPR

Hublet,

Basin,

Krstić

2024

Lecture Notes in Computer Science

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“…More complex examples can be found in the formalization of article 13 of the GDPR, which is described in [6].…”

Section: The Annotation Editormentioning

confidence: 99%

Towards Transparent Legal Formalization

Libal

Novotná

2021

Explainable and Transparent AI and Multi-Agent Systems

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A key challenge in making a transparent formalization of a legal text is the dependency on two domain experts. While a legal expert is needed in order to interpret the legal text, a logician or a programmer is needed for encoding it into a program or a formula. Various existing methods are trying to solve this challenge by improving or automating the communication between the two experts. In this paper, we follow a different direction and attempt to eliminate the dependency on the target domain expert. This is achieved by inverting the translation back into the original text. By skipping over the logical translation, a legal expert can now both interpret and evaluate a translation.

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Paradata as a Tool for Legal Analysis: Utilising Data-on-Data Related Processes

Enqvist

2024

Knowledge Management and Organizational Learning

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This chapter explores aspects of the relationship between technology, transparency, and accountability in public decision-making. It addresses how technological advancements have increased accessibility and automation while complicating decision process reviewability. It explores transparency as a relational concept and focuses on legal obligations on documentation and records-keeping, such as in the EU General Data Protection Regulation and the upcoming EU Artificial Intelligence Act, as a means to bolster transparency and improve reviewability. In particular it also discusses the feasibility of gathering and analysing ‘paradata’—data pertaining to data processes—as a means to safeguard legality and transparency in automated decision-making, notably within the public sphere.

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Towards Automated GDPR Compliance Checking

Cited by 5 publications

References 19 publications

Enforcing the GDPR

Enforcing the GDPR

Towards Transparent Legal Formalization

Paradata as a Tool for Legal Analysis: Utilising Data-on-Data Related Processes

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