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What Is Zero-Knowledge Proof and What Are Its Use Cases in Crypto?
Intermediate
2025-07-11 | 10m
Zero-knowledge proofs (ZKPs) are a cryptographic method used to prove knowledge about a piece of data, without revealing the data itself.
This article examines how zero-knowledge proofs function to ensure privacy, outlining their key advantages for users. It also highlights a range of blockchain use cases that utilize ZKPs.
What is Zero-Knowledge Proof (ZKP)?
While the inherent transparency of blockchains offers advantages in many scenarios, there are also numerous smart contract applications that necessitate privacy due to various business or legal considerations—such as using proprietary data as inputs to trigger smart contract execution. An increasingly prevalent approach to maintaining privacy on public blockchain networks is through zero-knowledge proofs (ZKPs). ZKPs enable one party to cryptographically demonstrate to another that they possess knowledge of a particular piece of information without revealing the actual data. In blockchain contexts, a ZKP disclosed on-chain confirms that a specific piece of information is valid and known by the prover with high certainty, without exposing the underlying details.
Needless to say, this intricate mechanism (interactive and non-interactive) will create many novel, interesting use cases, especially in industries where privacy is valued above most other things -
cryptocurrency comes to mind.
How Do Zero-Knowledge Proofs Work
At a high level, zero-knowledge proof works by having the verifier ask the prover to perform a series of actions that can only be performed accurately if the prover knows the underlying information. If the prover is only guessing as to the result of these actions, then they will eventually be proven wrong by the verifier’s test with a high degree of probability.
Zero-knowledge proofs were first described in a 1985 MIT paper from Shafi Goldwasser and Silvio Micali called “The Knowledge Complexity of Interactive Proof-Systems”. In this paper, the authors demonstrate that it is possible for a prover to convince a verifier that a specific statement about a data point is true without disclosing any additional information about the data. ZKPs can either be interactive—where a prover convinces a specific verifier but needs to repeat this process for each individual verifier—or non-interactive—where a prover generates a proof that can be verified by anyone using the same proof.
The three fundamental characteristics that define a ZKP include:
Completeness: If a statement is true, then an honest verifier can be convinced by an honest prover that they possess knowledge about the correct input.
Soundness: If a statement is false, then no dishonest prover can unilaterally convince an honest verifier that they possess knowledge about the correct input.
Zero-knowledge: If the state is true, then the verifier learns nothing more from the prover other than the statement is true.
Imagine a computational circuit that outputs a value on a curve, for a given input. If a user is able to consistently provide the correct answer to a point on the curve, one can be assured the user possesses some knowledge about the curve since it becomes increasingly improbable to guess the correct answer with each successive challenge round. Being able to prove knowledge about a data point without revealing any additional information besides knowledge of data provides a number of key benefits, especially within the context of blockchain networks.
Zero Knowledge vs. Zero Trust
“Zero knowledge” refers to the specific cryptographic method of zero-knowledge proofs, while “zero trust” is a general cyber security model used by organizations to protect their data, premises, and other resources.
The zero-trust framework assumes that every person and device, both internal and external to the network, could be a threat due to malicious behavior or simple incompetence. To mitigate threats, zero-trust systems require users and devices to be authenticated, authorized, and continuously validated before access to resources is granted.
Zero-knowledge proofs can be used as part of a zero-trust framework. For example, zero-knowledge authentication solutions can allow employees to access their organization’s network, without having to reveal personal details.
zk-SNARKs vs. zk-STARKs
zk-SNARK stands for zero-knowledge Succinct Non-Interactive Argument of Knowledge, with its highlight in non-interactive, meaning that anyone can verify a statement without interacting with the prover. This allows a blockchain network to verify the ownership of accounts, as well as ensure that the sender in a given transaction has sufficient balance without revealing addresses or transaction amounts.
Random elliptic curves are at the center of zk-SNARKs’ security model. A trusted setup is also required to kickstart a protocol using zk-SNARKs. This involves creating private keys that are later used to create proofs for transactions and verifications. As a result, zk-SNARKs are subject to quantum attacks and private key leaks. That said, zk-SNARKs can significantly reduce block sizes and gas consumption and have already accrued a large community since its inception in 2012.
zk-STARKs, which stands for zero-knowledge Scalable Transparent Argument of Knowledge, was introduced in 2018. As the name suggests, zk-STARKs focus on scalability and transparency. zk-SNARKs’ prover and verifier times increase linearly with witness size but in the case of zk-STARKs, it does so quasilinearly, making them far more agile when handling large datasets. zk-STARKs also leverage on publicly verifiable randomness and hash functions, which means they do not require an initial trusted setup and are quantum resistant.
That said, zk-STARKs generate far larger blocks and require much more computing power, which translates into more gas consumption and longer verification time. zk-STARKs also have far fewer developers and available resources compared to its older brother.
What are ZKP’s Use Cases in Crypto?
Proof of Identity
There is no place with a higher concentration of private data than our identity information. Traditionally, a proof of identity requires the prover-you-to submit your identity information-everything about you, relevant or not, in shocking details-to the verifier.
With ZKPs, on the other hand, all you need to do is generate a credential that serves as proof of the ownership and soundness of your identity. Verifiers need only perform some calculations to check the validity of your credential, instead of having access to all your personal information.
Merkle Tree Proof of Reserves
A Merkle Tree is a binary tree with data stored in its leaves. Each leaf has its own hash value and these hash values will be sorted into different groups (nodes) for further hashing until there is only one value - the root hash.
Verifiers need only take hash values from several nodes to verify the integrity of everything in the Merkle Tree without diving into a sea of 1s and 0s. This is widely used in proving an exchange has sufficient reserved funds and did not move their traders’ funds elsewhere for unspeakable purposes.
CoinCatch has always prioritized our customers and our Merkle Tree Proof of Reserves is available for everyone to verify:
CoinCatch’s Proof of Reserves.
For more information about our Merkle Tree Proof of Reserves, refer to our introduction to
Merkle Tree.
Zk-rollups
A rollup, as its name suggests, is a scaling solution that rolls up a collection of transactions into one. This enables much faster and cheaper transactions than, say,
Ethereum’s mainnet. There are two factions in Ethereum’s rollup solutions: Optimistic and Zero-knowledge. We will focus on the latter in this article.
Zero-knowledge rollups (zk-rollups) run computation off-chain and submit only a validity proof (a ‘summary’ of all rolled-up transactions) on-chain. Once this proof is verified on-chain, all rolled-up transactions will be finalized in one stroke.
There are several major players in Ethereum’s zk-rollup solutions.
Polygon announced that their zkEVM mainnet beta is set to launch in late March. In an effort to counter Polygon, zkSync -another contestant - opened up registration for developers on their ‘mainnet’ just one day after Polygon’s announcement.
CoinCatch Team
Disclaimer:
Digital asset prices carry high market risk and price volatility. You should carefully consider your investment experience, financial situation, investment objectives, and risk tolerance. CoinCatch is not responsible for any losses that may occur. This article should not be considered financial advice.
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