Today’s digital age requires financial institutions to balance consumer privacy with regulatory compliance. Zero-knowledge proofs (ZKPs) may be the solution to this problem. Crypto investors may maintain their privacy by utilizing ZKP technology, while institutions can utilize it to bridge traditional funds onto public blockchains. At the same time, it can be used as a potent tool for blockchain scalability without compromising decentralization. Is ZKP ushering in a new era of privacy-focused innovation?
Let’s explore more about ZKP in this article.
What is Zero-Knowledge?
A zero-knowledge proof is a method of establishing the truth of a proposition without exposing it. The ‘prover’ is the party attempting to prove a claim, whereas the verifier confirms the claim. Zero-knowledge protocols were first proposed in 1985 by legal theorist Richard Schaumberg in his book “The Knowledge Complexity of Interactive Proof Systems“.
How does it work?
Zero-knowledge protocols allow you to prove the truth of a proposition without revealing any information about the source of your knowledge or how you got the fact. Zero-knowledge protocols rely on algorithms that take some data as input and produce either true or false output.
All zero-knowledge proofs must meet three requirements:
- Completeness: The verifier can confirm the prover’s statement by verifying that it is true without having to know anything about its source.
- Soundness: The statement cannot be faked, and the verifier cannot be convinced that it was faked by someone who did not have the necessary information.
- Zero-Knowledge: The verifier will have no knowledge of anything other than the statement itself. The details of the information and personal data of the third parties are kept private.
A zero-knowledge proof consists of three components: a witness, a challenge, and a response.
- Witness: For the proof to work, the prover must be able to prove knowledge of some hidden information. The “witness” to the proof is the secret information and the prover’s knowledge of it produces a series of questions that can only be answered by a party who knows that information. In order to prove one’s knowledge, one must ask a question at random–and pass it on to another party.
- Challenge: The verifier asks the prover a new question at random from the set, and then the prover answers it.
- Response: The prover accepts the query and returns the answer to the verifier. The response allows the verifier to determine whether the latter has access to the first. During this conversation, more questions are asked so that the prover does not guess blindly and receives correct answers by chance. Repeated exchanges make it less likely for provers to forge knowledge from a witness.
Consider a situation in which you want to sell your secret code to Mrs X, who wants to enter the tunnel. You know the secret code and want to sell it to her, but she wants proof that you understand it before she pays you. You can do so by having her stand in front of the tunnel and watching you walk into one of the entrances and out of the other.
Types of Zero-Knowledge
ZK-SNARK stands for Zero-Knowledge Succinct Non-Interactive Knowledge of Argument. The ZK-SNARK protocol possesses the following characteristics:
- Zero-knowledge verification: A verifier determines the truth or falsity of a statement, without knowing anything else about it. The verifier understands whether the statement is true or false based on how it makes him or her feel.
- Succinct: To sum up, the zero-knowledge proof takes less time than a witness and can be validated quickly.
- Non-interactive: A non-interactive proof is a type of proof that requires one-time communication between the prover and verifier.
- Argument: As the proof meets the soundness criteria, it is unlikely that cheating will occur.
- (Of) Knowledge: Without access to the hidden information (witness), a prover cannot produce a zero-knowledge proof. A prover who does not have the witness will find it difficult, if not impossible, to compute a proper zero-knowledge proof.
ZK-STARK stands for Zero-Knowledge Scalable Transparent Argument of Knowledge. ZK-STARKs are similar to ZK-SNARKs, but they are:
- Scalable: In the case of Zk-STARK, proofs are verified quicker than SNARK proofs when the witness size is bigger.
- Transparent: Instead of relying solely on a trusted setup, ZK-STARK generates public parameters using publicly verifiable randomness. This makes the technology more transparent than ZK-SNARKs.
ZK-STARKs, which are based on the concept of zero-knowledge proofs, generate larger proofs than ZK-SNARKs. This implies that they have higher verification overheads. However, in some instances (such as proving enormous datasets), ZK-STARKs may be more cost-effective than ZK-SNARKs.
Use-cases of Zero-Knowledge Proofs
- Anonymous Transactions
Privacy-focused blockchains employ zero-knowledge technologies to enable nodes to validate transactions without having access to transaction data. Anonymizing transactions on public blockchains are also using zero-knowledge proofs. Tornado Cash, a decentralized, non-custodial service that allows users to execute private transactions on Ethereum, is one example. Tornado Cash employs zero-knowledge proofs to conceal transaction details and ensure financial privacy. Unfortunately, because these are “opt-in” privacy solutions, they are linked to illegal conduct. To address this, privacy must eventually become the default setting on public blockchains
- Identity Theft Prevention
Personal information is at risk when identity management systems are used. Individuals can use zero-knowledge proofs to confirm their identities and protect sensitive information, in a decentralized identity setting. Zero-knowledge proofs are especially useful for self-sovereign identification because they allow individuals to regulate access to personal identifiers without revealing sensitive information like tax ID numbers or passports.
Online services require users to establish their identities, which often involves providing personal information such as names, addresses and birth dates. Users may also need to memorize long passwords if they don’t want to lose access. However, zero-knowledge proofs can make authentication easier for both platforms and users by allowing them to submit a single proof that verifies their identity without revealing any private information about themselves. This improves the user experience and relieves organizations of the need to keep massive volumes of user data.
- Verifiable Computation
Another way to improve blockchain architectures is to use zero-knowledge technology. Verifiable computing allows us to delegate computation to another entity while ensuring the results are verifiable. The entity submits the outcome together with verification that the program was correctly performed. Verifiable computing is crucial for increasing blockchain processing speeds while maintaining security.
Drawbacks of Zero-Knowledge Proofs
- Hardware expenses
Creating zero-knowledge proofs requires extremely sophisticated calculations that are best conducted on specialized devices. These expensive devices are rarely available, and they can cost thousands of dollars. Furthermore, applications that intend to access zero-knowledge technology must consider hardware expenditures, which may raise end-user costs.
- The expense of proof verification
Verifying proofs, which are necessary for zero-knowledge technologies to work, requires a lot of math. This increases the cost of incorporating ZK-STARKs into applications. For example, verifying an individual ZK-SNARK proof on Ethereum costs 500,000 gas; verifying a single ZK-STARK proof requires even higher fees.
- Assumptions of Trust
In the zero-knowledge protocol, a Common Reference String (CRS) is generated once and then made available to other parties wishing to participate in the protocol. A trusted setup ceremony is used for generating the CRS. However, no mechanism exists for users to check the honesty of participants, so users must take the developers’ word for it. Because the randomness employed to generate the string is publicly verifiable, ZK-STARKs are devoid of trust assumptions. On top of that, researchers are working on non-trusted ZK-SNARK setups that would improve security even further.
- Quantum Computing Threats
In elliptic curve cryptography (ECDSA), the key is formed by hashing multiple random binary numbers. As its name suggests, this method is considered more secure than other forms of cryptography because it’s resistant to being broken by quantum computing methods.
Future of ZK
The popularization of ZKP technology is a sign that traditional financial systems will eventually be integrated with the growing realm of decentralized apps (DApps), which offer decentralized technologies. However, while businesses and consumers can now use trustless technologies without worrying about the security of their data, they’ll still need to keep an eye on it closely and consistently.
Zero-knowledge proofs are an emerging technology that has been gaining traction in blockchain, bitcoin, and DeFi. Because they protect privacy while allowing for scalable systems, zero-knowledge proofs are likely to play a critical role in developing more secure, private, and efficient DApp ecosystems.