Discover zero-knowledge proofs and ZoKrates. Learn their role in enhancing smart contract security, how ZoKrates aids their integration in decentralized apps, their functionality, types, and uses.

The vision of blockchain technology has always been a world where transactions are completely private and secure, while also being executed at lightning speed. Unfortunately, achieving this utopia has always come at the cost of scalability and privacy. Zero-knowledge proofs (ZKPs) are a revolutionary cryptographic protocol that enable secure and private interactions between parties, without revealing sensitive information. They offer a great solution to the current limitations of blockchains, as they are tailored for scalability and privacy.

In this article, we provide a comprehensive overview of ZKPs and ZoKrates, including their features, applications, and step-by-step instructions on how to build a smart contract using ZoKrates. We will also explore the benefits and limitations of ZoKrates, and discuss the potential for future developments in the field.

By definition, ZKPs are a powerful cryptographic protocol that enable one party to prove to another that they know a secret without revealing the secret itself. One area where ZKPs have gained popularity in recent years is smart contracts.

ZKPs have become an invaluable tool for ensuring privacy and security in smart contracts. By enabling parties to prove the validity of certain statements without revealing any additional information, ZKPs can be used to authenticate data such as a user's age without revealing their actual age. Additionally, ZKPs can facilitate secure and private interactions between parties, eliminating the need for intermediaries or manual verification processes.

Another benefit of ZKPs is that they increase efficiency by streamlining the verification process. This is achieved by eliminating the need for intermediaries or manual verification processes. Furthermore, ZKPs enhance security by providing a more secure way to authenticate and verify information, as the information is not revealed to third parties. This reduces the risk of unauthorized access, manipulation, or theft of sensitive information, making ZKPs a valuable tool for smart contract applications where security and privacy are critical.

ZoKrates is an open-source toolbox for zk-SNARKs on Ethereum, providing developers with an easy-to-use programming language and a compiler that allows them to write and verify ZKPs. With integrated Ethereum support, ZoKrates enables developers to create smart contracts that use ZKPs.

It is built on Rust and the zk-SNARK protocol, and offers tools for circuit optimization, proof generation, and verification, enabling developers to create secure and scalable applications with enhanced privacy. The verification of ZKPs generated using ZoKrates is achieved by running the ZoKrates verifier contract on the Ethereum blockchain.

ZoKrates has a variety of potential applications, including privacy-preserving identity systems, voting systems, supply chain management, and decentralized finance (DeFi) applications.

One of the biggest benefits of using ZoKrates is that it makes it easy for developers to integrate ZKPs into their decentralized applications (dapps). The library provides a set of tools for generating and verifying ZKPs, so developers don't have to write the code themselves.

Another key benefit of ZoKrates is its accessibility, as it is designed to be user-friendly for developers of all levels. Additionally, the library is highly customizable, allowing developers to tailor proofs to their specific use cases.

As mentioned earlier, ZKPs allow one party (the prover) to demonstrate to another party (the verifier) that a certain statement is true, without revealing any additional information beyond the truth of the statement itself. This can be a powerful tool for privacy-preserving computation, as it allows for the verification of sensitive information without revealing that information to third parties. This can be achieved through a variety of mathematical techniques, including the use of elliptic curve cryptography and advanced cryptographic hash functions.

In order for a zero-knowledge (zk) protocol to be valid, it must meet three key criteria: completeness, soundness, and zero-knowledge. Completeness ensures that the protocol returns "true" for valid inputs, while soundness guarantees that it is impossible to fool the protocol with invalid inputs. Zk ensures that the verifier does not learn any information beyond the validity or falsity of the statement being proved, and that they cannot derive the original input from the proof.

A ZKP will also consist of three key elements: the witness, challenge, and response. The witness is the hidden information that the prover wants to prove knowledge of. The prover establishes a set of questions that can only be answered by someone with knowledge of the witness, and begins the proving process by randomly choosing a question, calculating the answer, and sending it to the verifier. The verifier then randomly chooses another question and asks the prover to answer it, and the prover responds with the correct answer. This process is repeated many times until the verifier is satisfied that the prover really does have knowledge of the witness.

There are several different types of ZKPs, each with their own strengths and weaknesses. Some of the most commonly used types include:

●  zk-SNARKs (Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge) – These are highly efficient proofs that can be used to verify complex computations. They have been used in applications such as cryptocurrency transactions and blockchain-based smart contracts.

●  zk-STARKs (Zero-Knowledge Succinct Transparent Arguments of Knowledge) – These are similar to zk-SNARKs but do not rely on trusted setup procedures. They are often used in applications where trust in the underlying technology is a key concern.

●  Bulletproofs – These are a newer type of ZKP that offer both efficiency and flexibility. They have been used in applications such as secure messaging and privacy-preserving data sharing.

ZKPs have a wide range of applications in various fields, including finance, healthcare, and government. Some of the most notable use cases include:

●  Privacy-preserving transactions on blockchain networks such as Ethereum. By using zk-SNARKs, it is possible to verify the validity of transactions without revealing any sensitive information about the parties involved.

●  Secure messaging and data sharing in healthcare. By using ZKPs, it is possible to verify the authenticity of medical records and other sensitive information without compromising patient privacy.

●  Secure voting systems. By using zk-SNARKs, it is possible to verify the validity of votes without revealing the identity of the voters.

In recent years, there have been several successful implementations of ZKPs in real-world applications. For example, the Zcash cryptocurrency uses zk-SNARKs to enable anonymous transactions on its blockchain. Another notable example is the Tornado Cash privacy protocol, which uses zk-SNARKs to enable private transactions on the Ethereum network.

The Zokrates library provides an easy-to-use interface for generating ZKPs, making it simple to integrate them into your smart contracts.

Let’s walk through the steps to use ZoKrates to generate a ZKP for a password guessing game. We will start by defining the circuit that represents the game, compile it using ZoKrates, and then generate a verification key and proof. Finally, we will show how to integrate the proof into a smart contract, allowing users to prove that they know the correct password without revealing it.

• First, write the program in ZoKrates' DSL: We want to create a smart contract that checks whether a user's password is valid without revealing the password itself. You can write a program in ZoKrates' DSL that takes in the user's password as input and outputs a boolean value indicating whether the password is valid or not.

def main(private field password, private field[] guess) -> (field):

field[256] memory secret = sha256(concat(password, "secret salt")) field[256] memory hashed_guess = sha256(concat(guess, "guess salt")) field[1] memory result = 1for i in 0..255 do

if mul(sub(1, secret[i]), hashed_guess[i]) != 0 then

result = 0

break endIf

return result

This program takes in a private password field and a private array of guess fields, and concatenates them with secret and guess salts respectively. It then hashes the concatenated values using SHA-256, and compares each byte of the secret hash to the corresponding byte of the guess hash. If any byte doesn't match, the program returns 0 indicating an invalid password. Otherwise, it returns 1 indicating a valid password.

• Compile the program into an arithmetic circuit using the ZoKrates compiler. To do this, run the following command in your terminal:

zokrates compile -i <program>.zok

This will create a set of .code, .out, and .pk files that represent our compiled program.

• Generate the proving and verification keys using the ZoKrates key generator to create proving and verification keys.

zokrates setup

This will create two files: a proving key (proving.key) and a verification key (verification.key).

• Hash the circuit: To generate a proof that can be verified on a smart contract platform, we'll need to hash our circuit. Run the following command in your terminal to generate the hash:

zokrates export-verifier 							

• Write and deploy the smart contract:

pragma solidity ^0.8.0;
                                 
contract PasswordVerifier { address private verifier; bytes32 private hash;
                                 
constructor(address _verifier, bytes32 _hash) { verifier = _verifier;
 hash = _hash;
                                 
}
                                 
function verifyPassword(uint256[] calldata _proof, uint256 _password, uint256[] calldata _guess) public view returns (bool) {
return IVerifier(verifier).verify(hash, _proof, [_password] ,_guess); }
}
interface IVerifier {
 function verify(bytes32 _hash, uint256[] calldata _proof, uint256[] calldata _inputs, uint256[]
calldata _witness) external view returns (bool);}

The contract takes in the verifier address and the hashed circuit as input, and provides a method called verifyPassword that allows users to submit their password and guess array along with a ZKP.

• Verify the proof: When a user submits their password, guess array, and proof to the smart contract, the contract should use the verification key to validate the proof. If the proof is valid, the contract will return true indicating that the password is valid without revealing the actual password.

function verifyPassword(uint256[] calldata _proof, uint256 _password, uint256[] calldata _guess) public view returns (bool) {

return IVerifier(verifier).verify(hash, _proof, [_password] ,_guess); }

The function takes in the ZKP, password, and guess array as input, and uses the IVerifier interface to call the verify function with the hashed circuit, proof, and inputs. If the verification succeeds, the function will return true indicating that the password is valid.

• Generate the proof: To generate a ZKP, a user will need to run the following commands in their terminal:

zokrates compute-witness -a <password> <guess[0]> <guess[1]> ... <guess[n]> zokrates generate-proof

The compute-witness command takes in the password and guess array as input and generates a witness for our program. The generate-proof command then uses the witness to generate a ZKP.

• Submit the proof: The user can now submit the ZKP, password, and guess array to the smart contract using the verifyPassword function. If the proof is valid, the contract will return true indicating that the password is valid without revealing the actual password.

In this beginner's guide, I have introduced you to the world of ZKPs and shown you how to use the ZoKrates library to implement them in your smart contracts. ZKPs are a powerful tool for adding an additional layer of privacy and security to your applications, particularly in blockchain applications where trust and security are essential. With the ZoKrates library, it is easy to integrate ZKPs into your dapps, and we hope this guide has given you a solid foundation for exploring this exciting area of cryptography and blockchain development.