Data Privacy for Digital Asset Systems

Data privacy in digital asset systems is of sustained importance to end users. However, there can be disconnect between an end users' expectations of privacy while using a digital asset payment system and the system's actual treatment of collected, stored, and used data. This paper provides foundational primer on data privacy alongside qualitative and technical assessments of various approaches to data privacy frameworks and strategies relevant to the early stages of a digital asset system's design. Analysis relies initially on an outlay of foundational data privacy concepts, including anonymity, confidentiality, and full disclosure, alongside three differing approaches to data privacy frameworks. Analysis finds that some concepts, such as a desire for cash-like anonymity are based on false underlying assumptions. The paper moves away from a likely unattainable standard of anonymity and instead focuses on a hybrid approach to data privacy, inclusive of Cavoukian's privacy-by-design and popular applications of privacy-by-policy. This hybrid approach is visualized with a technical comparison of privacy-enhancing technologies (PET) across architectural layers, detailing both popular and emerging PETs relevant to digital asset systems which prioritize a hybrid approach to confidentiality. The paper further finds that a particular combination of popular and emerging technologies may provide as-yet untested but novel benefits to maintaining strong confidentiality – and possibly end users' expectations of privacy - while data is under audit. A nuanced approach, rather than a reliance on a singular novel PET or dubious assurances of anonymity, may best facilitate strong confidentiality with sustainable end-user privacy protections for digital asset system users.