Privacy-Preserving Techniques for Trustworthy Data Sharing: Opportunities and Challenges for Future Research

Abstract

One of the foundations of data sharing in the European Union (EU) is trust, especially in view of the advancing digitalization and recent developments with respect to European Data Spaces. In this chapter, we argue that privacy-preserving techniques, such as multi-party computation and fully homomorphic encryption, can play a positive role in enhancing trust in data sharing transactions. We therefore focus on an interdisciplinary perspective on how privacy-preserving techniques can facilitate trustworthy data sharing. We start with introducing the legal landscape of data sharing in the EU. Then, we discuss the different functions of third-party intermediaries, namely, data marketplaces. Before giving a legal perspective on privacy-preserving techniques for enhancing trust in data sharing, we briefly touch upon the Data Governance Act (DGA) proposal with relation to trust and its intersection with the General Data Protection Regulation (GDPR). We continue with an overview on the technical aspects of privacy-preserving methods in the later part, where we focus on methods based on cryptography (such as homomorphic encryption, multi-party computation, private set intersection) and link them to smart contracts. We discuss the main principles behind these methods and highlight the open challenges with respect to privacy, performance bottlenecks, and a more widespread application of privacy-preserving analytics. Finally, we suggest directions for future research by highlighting that the mutual understanding of legal frameworks and technical capabilities will form an essential building block of sustainable and secure data sharing in the future

Strategic Medical Affairs Outsourcing: Pragmatic Solution In A Fast-Changing And Resource-Constrained World

“…Secure file sharing, strong encryption, and compliance with data protection laws guarantee the security and integrity of sensitive information shared between pharmaceutical businesses and their outsourcing partners. [18]…”

Children’s Privacy and Video Games: Comments on Commercial Surveillance ANPR, R111004

“…It also allows for innovative, privacy-preserving data analysis techniques such as di erential privacy, homomorphic encryption, and federated learning to be used if the conditions allow. 106 To ensure e ectiveness of such an approach, we recommend rules that require the appointment of a children's privacy o cer (CPO) in every company. Taking inspiration from the GDPR's requirement of a data protection o cer, the CPO should be responsible for understanding the interface of the company's business practices with children's privacy rules.…”