Balancing AI innovation and data privacy: the role of synthetic data and privacy-enhancing technologies in GDPR compliance

Sav, Sultan Damla (A.A. 2023/2024) Balancing AI innovation and data privacy: the role of synthetic data and privacy-enhancing technologies in GDPR compliance. Tesi di Laurea in Data protection law, Luiss Guido Carli, relatore Filiberto Brozzetti, pp. 45. [Master's Degree Thesis]

Full text for this thesis not available from the repository.

Abstract/Index

Literature review. Understanding synthetic data: definitions and data: and compliance implications. Definition and purpose of PETs. GDPR Key principles and limitations for privacy-enhancing technologies. Methodology. Research approach. Data sources and legal frameworks. Analytical framework. Results & discussion. Exploring GDPR and the AI act. Practical benefits and sector-specific applications. Privacy-enhancing technologies: implementation challenges. Privacy-enhancing technologies in practice. Healthcare and financial services: AI, GDPR, and PETs in practice. Bridging AI innovation and data privacy: ethics, governance, and future trends. Bridging the gap between GDPR and AI innovation. Regulatory sandboxes and future compliance strategies.

References

Bibliografia: pp. 41-45.

Thesis Type: Master's Degree Thesis
Institution: Luiss Guido Carli
Degree Program: Master's Degree Programs > Master's Degree Program in Digital Innovation and Sustainability (LM/SC – GIUR)
Chair: Data protection law
Thesis Supervisor: Brozzetti, Filiberto
Thesis Co-Supervisor: Catanzariti, Mariavittoria
Academic Year: 2023/2024
Session: Extraordinary
Deposited by: Alessandro Perfetti
Date Deposited: 08 Jul 2025 07:40
Last Modified: 08 Jul 2025 07:40
URI: https://tesi.luiss.it/id/eprint/42778

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