MACROPRIVACY

Research Summary

This report explores data privacy in digital asset systems, analyzing different approaches to data privacy frameworks. It suggests a hybrid approach that includes privacy-by-design and privacy-by-policy. The report also discusses the relevance of privacy-enhancing technologies (PET) to digital asset systems and how they can provide novel benefits to maintaining strong confidentiality and end-user privacy.

Key Takeaways

Understanding Data Privacy in Digital Asset Systems

  • Importance of Data Privacy: Data privacy in digital asset payment systems protects users from identity theft, discrimination, and public scrutiny of personal spending habits. Balancing risk mitigation measures and end-user privacy expectations is a challenging task for these systems.
  • Privacy-by-Design and Privacy-by-Policy: Two basic frameworks for data privacy strategies are privacy-by-design, which involves shaping the system’s architecture with privacy as a priority, and privacy-by-policy, which focuses on implementing business practices that promote informed consent for data handling.
  • Hybrid Approach to Data Privacy: The report suggests a hybrid approach that combines elements of privacy-by-design and privacy-by-policy can provide comprehensive data protections for a digital asset system.

Challenges and Misconceptions in Data Privacy

  • False Equivalency: Comparing the privacy of physical banknotes to digital assets is a false equivalency, as digital assets collect more data and require connections to information systems.
  • Difficulty in Maintaining Anonymity: Anonymity in a digital asset system is difficult to maintain, as even systems that do not require the collection of identification data may still collect and log some data by default.
  • Confidentiality and Full Disclosure: Confidentiality in a digital asset system implies that collected and stored data is protected from view and available only to authorized actors. Full disclosure means that collected and stored data is not protected from view by any system user.

Privacy-Enhancing Technologies (PET)

  • Foundational PET: Foundational Privacy-Enhancing Technologies (PET) can be included in the design of a digital asset payment system. These include encryption, digital signatures, and ring signatures.
  • Advanced PET: Advanced privacy technologies like secure multi-party computations (MPC), fully homomorphic encryption, and zero-knowledge proofs (ZKPs) can help balance data privacy preservation and auditing.
  • Combining PET: Combining privacy models and novel PETs can automate data analysis and auditing while protecting user privacy. More research is needed to determine the best combination of these techniques for privacy protection in large data sets.

Data Privacy Techniques in Digital Payment Systems

  • Records Management Approaches: Records management approaches, including collection limitations and retention limitations, help ensure confidentiality.
  • Selective Revelation and Redaction: Selective revelation and selective redaction are techniques to limit the exposed data shown to others.
  • Privacy Coins: Privacy coins like Monero and Zcash integrate data protection methodologies and technologies to keep user data confidential.

Considerations for a Data Privacy Strategy

  • Network Architecture: The network architecture of a digital asset determines the locations of data touchpoints and the types of data processed. Permissionless and permissioned digital asset payment networks have different privacy implications.
  • Selective Disclosure: Selective disclosure empowers users to maintain control over their data and decide which pieces to share or keep confidential.
  • Performance Goals: Performance goals, such as transactions per second, may impact the choice of privacy technologies and techniques in a digital asset network.

Actionable Insights

  • Adopt a Hybrid Approach: Digital asset systems should consider adopting a hybrid approach that combines elements of privacy-by-design and privacy-by-policy for comprehensive data protection.
  • Investigate the Potential of PET: More research is needed to explore the potential of combining different privacy-enhancing technologies (PET) for optimal privacy protection in digital asset systems.
  • Consider Network Architecture: When designing a digital asset system, consider the network architecture and its implications for data privacy.
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