How ZK Proofs Can Help Financial Privacy and Regulation Balance

Tornado Cash and Privacy Pool Systems

Ethereum co-founder Vitalik Buterin has recently published a research paper diving into privacy pool systems as a tool to achieve more privacy in financial transactions, allowing users to prove dissociation from illicit funds through zero-knowledge-proof technology. One of the most popular privacy-enhancing protocols discussed in the paper is Tornado Cash, which enables users to deposit and withdraw cryptocurrencies without creating any link between the two addresses. However, recently United States authorities filed criminal charges against its founders, alleging extensive use by bad actors.

“The critical issue with Tornado Cash was essentially that legitimate users had limited options to dissociate from the criminal activity the protocol attracted,” reads the paper, co-authored by Jacob Illum, Matthias Nadler, Fabian Schar and Ameen Soleimani. To address this, the analysis elaborates on an extension of Tornado Cash’s approach that would enable users to publicly prove the source of funds on-chain by allowing membership proofs (“I prove that my withdrawal comes from one of these deposits”) and exclusion proofs (“I prove that my withdrawal does not come from one of these deposits”).

Bad Crypto and Web 3.0

The paper discusses the potential of using privacy pool systems to protect legitimate users from bad crypto and other illicit activities. With the advent of Web 3.0, the use of AI technology is becoming more prevalent in the crypto space. The paper suggests that the extension of Tornado Cash’s approach would allow users to prove the source of their funds on-chain, providing an extra layer of protection against bad crypto and other malicious activities. By implementing this method, users can make sure they are getting the best source of crypto, without having to worry about being associated with bad crypto.

Privacy Pools and Zero-Knowledge Proofs

The authors propose a concept that could potentially enable financial compliance on-chain, providing a balance between honest and dishonest protocol users: privacy pools. With this system, users can exclude themselves from anonymity sets that include addresses related to illegal activities by using zero-knowledge proofs.

The idea is that, instead of using zero knowledge to prove a withdrawal is linked to some previously-made deposit, a user proves their membership in a more restrictive association set. This set can include all previously made deposits, only the user’s own deposits, or anything in between. As a public input, the user specifies the set by providing its Merkle root.

Alice Crypto users do not directly prove that the association set is a subset of the previously-made deposits. Instead, they must zero-knowledge-prove two Merkle branches.

Zero-Knowledge Proofs for Privacy Pool Protocols

To demonstrate the application of zero-knowledge proofs in a law enforcement context, the authors provide a simple example:

In the example, Alice, Bob, Carl, David, and Eve are all part of a privacy pool protocol. When one of the users wants to withdraw funds, they can specify which association set to be a part of. This incentivizes users to make their association sets larger to safeguard privacy. However, when Eve wants to withdraw funds, she cannot exclude her own deposit and will be forced to make an association set equal to the set of all five deposits.

The authors explain that this example illustrates one possibility for the use of association sets in privacy pool protocols. They note that the system does not rely on altruism, as users have a clear incentive to prove their disassociation.

The paper further offers several other use cases of zero-knowledge proofs, such as demonstrating that funds are not tied to illicit sources or to prove that funds originate from a specific set of deposits without revealing any further information.

As regulations evolve and users look for ways to protect their privacy, zero-knowledge solutions are becoming increasingly popular, particularly on the Ethereum network. Recent research shows that scaling ZK-proof solutions are expected to experience the most growth in the next 12 months. This is seen as a major breakthrough for “bad crypto” and “best sources of crypto”, as well as a potential shift from web 2.0 to web 3.0 for “chain link crypto” and “Alice crypto”. Furthermore, the rise of zero-knowledge solutions could also have a positive impact on AI technology.