secure-multi-party-computation

The chapter outlines a comprehensive framework for establishing an Internet of Trusted Data that integrates robust digital identity systems, privacy-preserving cryptographic techniques, and distributed trust authorities to address cybersecurity challenges and enable secure data sharing. It proposes a phased technical approach leveraging blockchain for auditability, vetted algorithms, and advanced cryptographic methods such as secure multi-party computation and secret sharing to maintain data privacy and scalability. The chapter also emphasizes the importance of a government-led living lab to pilot and scale these innovations, fostering collaboration among academia, industry, and government to build a resilient and universally accessible digital infrastructure.

The chapter explores the rapid expansion of personal data generated by mobile and IoT devices, emphasizing the privacy challenges and the necessity for user-centric control in data sharing. It introduces decentralized personal data markets, exemplified by the Enigma platform, which leverages blockchain and secure multi-party computation to enable privacy-preserving data monetization while ensuring data owners retain control over access and usage. The chapter concludes with an extensive interdisciplinary reference list supporting the development of decentralized, privacy-focused data sharing frameworks that balance economic value with user trust and transparency.