There seems to be a bit of misunderstanding here. When we refer to privacy, we mean “pure privacy,” a complete ownership of the data you’re committing, with access fully restricted and solely controlled by the owners. This level of privacy is crucial for private sector adoption. In contrast, any public blockchain privacy system inevitably relies on certain assumptions.
For instance, Trusted Execution Environments (TEEs) can provide affordable and somewhat “interoperable” privacy, yet they depend on hardware trust assumptions—suitable for some but not all users.
This is where trade-offs come into play, which is precisely what this report aims to highlight. Algorithmic privacy, for example, introduces additional complexity and limits the ability to interoperate with private datasets, as noted in the document. This forms the trilemma we emphasized earlier. We hope these clarifications add contrast to this complex privacy topic, where public blockchain privacy cannot provide a complete solution. True privacy requires exclusive ownership, restricted access, and computational encryption schemes whose complexity should adapt to the requirements of each participant in relation to the trilemma constraints.