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- a16z warns many ZK systems lack true privacy despite labels
- Jolt zkVM upgrade introduces blinded proofs to enable genuine privacy
- Debate grows as developers question meaning of zero knowledge technology
Growing interest in privacy focused blockchain technology has sparked renewed discussion across the developer community after a16z Crypto revealed what it considers a hidden weakness within many systems labeled as zero knowledge. The Web3 investment unit of Andreessen Horowitz wrote that a number of developer tools that are now being referred to as ZK systems do not in fact provide the privacy guarantees commonly implied by the name.
Recently, the a16z Crypto blog described how most zkVM implementations focus on the generation of small and fast verifiable proofs rather than making sure that sensitive information is fully obscured when verifying. Therefore, the company claimed that the term has been used by the industry more frequently in the form of shorthand zk instead of the initial meaning of a zero knowledge privacy.
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The firm says that with most zkVM designs, one needs an extra technical operation called wrapping to achieve actual zero knowledge properties, which do not allow leakage of information. This process is a recursive process that can be used to prove that a given proof is being verified by an already known proof within another proof system that facilitates the process of zero knowledge.
Nevertheless, this new process has created several problems to programmers who want to ensure that their processes remain efficient in addition to data privacy. The blog has pointed out that recursive wrapping processes tend to involve high computational overheads and can create trusted configurations that diminishes transparency.
Industry Debate Over the Meaning of Zero Knowledge
Debates about the appropriate use of the term zero knowledge have been on the rise among developers and researchers after the problem of privacy has gained traction in the cryptocurrency industry. Players in the industry feel that the lack of understanding of terms may slow privacy infrastructure.
In zero knowledge proofs, a prover is able to show that a statement is correct without showing the sensitive information on which that result was obtained. As a result, the verifier is able to verify the validity of the statement whereas the data behind it is confidential.
The cryptographic concept had been first developed by academic researchers several decades before the emergence of blockchain technology. The technology was later applied by cryptocurrency projects to deal with privacy problems in the public networks.
Among the first large scale applications, Zcash was one of the first to make use of zk SNARKs to obscure transaction data and still have the network verify the transfer. Since, a number of blockchain projects have followed the same approach.
Jolt zkVM Upgrade Introduces Native Privacy Features
In addition to the criticism of the current terminology, a16z Crypto also described a major upgrade to its open source Jolt zkVM, designed to overcome the privacy constraints of a few zkVM systems currently in use by developers.
Zero knowledge virtual machines enable programs to execute, and generate proofs that establish correct code implementation without disclosing sensitive program input information that was used in computation. This would allow them to be used in privacy sensitive blockchain applications.
Previous applications of Jolt were more interested in compact proofs generation that enabled efficient verifications but did not fully provide zero knowledge privacy protection of sensitive inputs.
To cope with this weakness, developers included a folding mechanism called NovaBlindFold, which forms blinded proofs to ensure no information is leaked in the process of verification.
NovaBlindFold Brings Privacy Without Major Performance Cost
The folding methodology applied to the upgrade is a result of the research that can be traced to the 1990s, but the current cryptographic systems have adjusted the method to address the blockchain verification setting.
When NovaBlindFold was incorporated by developers, Jolt was able to produce privacy preserving proofs and the verification performance of the tool remained relatively efficient with blockchain applications. The new system created an updated version of the evidence that is approximately three kilobytes bigger than the previous non zero knowledge version of Jolt, as stated in the blog post.
The developers thus view the increment as rather minor as opposed to the incremental privacy guarantees offered by the upgrade.
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