You are currently viewing Blockchain From Scratch: Exploring the Role of Zero-Knowledge Proofs |  by Radovan Stevanovic |  Coinmonks |  Jan, 2023

Blockchain From Scratch: Exploring the Role of Zero-Knowledge Proofs | by Radovan Stevanovic | Coinmonks | Jan, 2023

Blockchains are often associated with transparency and the public availability of information. However, there are certain use cases where this level of transparency is more desirable and necessary. This is where zero-knowledge proofs (ZKPs) come into play.

ZKPs are a type of cryptographic proof that allows one party (the prover) to prove to another party (the verifier) ​​that they possess certain information without revealing the actual information itself. This allows for privacy and confidentiality to be maintained while still being able to prove that something is true.

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One of the key benefits of ZKPs is their ability to enable confidential transactions on a public blockchain. This can be particularly useful when transmitting information that is sensitive or personal, such as medical records or financial data.

ZKPs can also enhance the security of a blockchain by allowing for verifiable, trustless authentication of transactions. This can help prevent fraud and ensure the integrity of the blockchain.

In addition, ZKPs has the potential to enable scalability improvements in blockchains. By allowing the verification of transactions without revealing all of the underlying data, ZKPs can reduce the amount of data that needs to be stored on the blockchain, making it more efficient and scalable.

Zero-knowledge-proof systems can be broadly classified into interactive and non-interactive.

Interactive Zero-Knowledge Proofs

Interactive zero-knowledge proofs, also known as zero-knowledge interactive proof systems (ZKIPs), involve a back-and-forth communication between a prover and a verifier. The prover tries to convince the verifier that a statement is true without revealing additional information.

One of the earliest examples of an interactive zero-knowledge proof is the Feige-Fiat-Shamir (FFS) protocol. In this protocol, the prover sends a random challenge to the verifier, and the verifier responds with a response. The prover then sends proof that the challenge and response are correctly related.

Non-Interactive Zero-Knowledge Proofs

Non-interactive zero-knowledge proof systems, also known as zero-knowledge succinct Non-Interactive Arguments of Knowledge (zk-SNARKs), involve a single message from the prover to the verifier. The prover creates a proof consisting of a public and a private component and sends the public component to the verifier. The verifier can then use the public component to verify the proof without additional communication.

One of the most well-known examples of a non-interactive zero-knowledge proof system is zk-SNARK, which stands for “Zero-Knowledge Succinct Non-Interactive Argument of Knowledge.” zk-SNARKs have been used in many blockchain projects, including Zcash and Ethereum.

Both interactive and non-interactive zero-knowledge-proof systems have their benefits and trade-offs. Interactive proof systems are generally faster and simpler to implement but require back-and-forth communication between the prover and verifier. Non-interactive proof systems are usually more efficient but more complex to implement and need a trusted setup.

There are several different types of ZKP systems, each with unique characteristics and applications.


ZK-SNARKs (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge) is a type of ZKP that allows for the creation of short, non-interactive proofs of the possession of certain information. This makes them particularly well-suited for use in high-throughput systems, such as blockchains.

The basic process of creating a ZK-SNARK proof involves the following steps:

  1. The prover generates a public/private key pair, with the public key used to verify the proof and the private key used to create the proof.
  2. The prover creates a “common reference string” (CRS) based on the public key, which will be used as the basis for the proof.
  3. The prover selects a “random seed” which will be used to create a “proving key” and a “verification key”. These keys are used to create and verify the proof, respectively.
  4. The prover creates proof by inputting the statement to be proven, the proving key, and the CRS into a proving algorithm.
  5. The prover sends the proof to the verifier, who inputs the proof, the verification key, and the CRS into a verification algorithm.
  6. If the verification algorithm returns “true,” the proof is valid, and the statement has been proven. If the verification algorithm returns “false”, the proof is invalid, and the statement has not been proven.

One of the key features of ZK-SNARKs is their ability to provide proof of possession without requiring any interaction between the prover and verifier. This makes them highly efficient and allows for a high degree of scalability.


STARKs (Scalable Transparent ARgument of Knowledge) is a type of ZKP based on polynomial commitments and requires interaction between the prover and verifier. Unlike ZK-SNARKs, STARKs does not require a trusted setup, making them more secure.

The basic process of creating a ZK-STARK proof involves the following steps:

  1. Preparation: The prover selects random parameters and generates proofing and verifying keys.
  2. Proving: The prover inputs their statement and the proof key into a proof algorithm, which outputs a proof.
  3. Verification: The verifier inputs the proof, the statement, and the verifying key into a verification algorithm, which either accepts or rejects the proof.
  4. Validation: If the proof is accepted, the verifier can be confident that the statement is true without learning any information about it.

In practice, ZK-STARK proofs are constructed using a combination of algebraic operations, hash functions, and error-correcting codes. The exact details of the construction depend on the specific implementation, but the basic process described above remains the same.

STARKs have been designed with scalability in mind and have the potential to enable faster and more efficient transaction processing on a blockchain. They have been used in several projects, including the Ethereum blockchain.


Bulletproofs are a type of ZKP designed to be efficient and easy to implement. They are based on elliptic curve cryptography and do not require a trusted setup.

The basic process of creating bulletproofs proof is as follows:

  1. The prover begins by selecting a random value, known as the blinding factor, and using it to compute a commitment to the statement they want to prove.
  2. The prover then constructs a proof of knowledge, using the commitment and the blinding factor as inputs. This proof demonstrates that the prover knows the statement without revealing any information about it.
  3. The prover sends the proof to the verifier, along with the commitment.
  4. The verifier checks the proof to ensure that it is valid and that the commitment is correct. If the proof is valid, the verifier can be confident that the prover knows the statement without learning any information about it.

Bulletproofs have been used in many blockchain projects, including the privacy-focused cryptocurrency Monero.

Zero-Knowledge Proof of Knowledge (ZKPoK)

Zero-Knowledge Proof of Knowledge (ZKPoK) allows a prover to demonstrate possession of certain knowledge to a verifier without revealing any information about it. One example of ZKPoK is the Fiat-Shamir transformation, which converts an interactive proof into a non-interactive proof using a cryptographic hash function.

Zero-Knowledge Proof of Identity (ZKPi)

Zero-Knowledge Proof of Identity (ZKPi) allows a prover to demonstrate ownership of a specific identity to a verifier without revealing any information about it. One example of ZKPi is the Schnorr signature scheme, which allows a prover to sign a message with their private key while allowing a verifier to verify the signature without learning the private key.

Zero-Knowledge Proof of Membership (ZKPM)

Zero-Knowledge Proof of Membership (ZKPM) allows a prover to demonstrate membership in a specific group to a verifier without revealing any information about their membership. One example of ZKPM is the membership test protocol, which allows a prover to demonstrate membership by providing a valid solution to a mathematical problem that group members can solve only.

Zero-Knowledge Proof of Equivalence (ZKPe)

Zero-Knowledge Proof of Equivalence (ZKPe) allows a prover to demonstrate to a verifier that two statements are equivalent without revealing any information about them.

In conclusion, zero-knowledge proofs provide privacy and security in blockchain technology. By allowing a prover to demonstrate knowledge or possession of certain information without revealing it, ZKPs enables the creation of secure and anonymous transactions and protocols.

As the use of blockchain technology continues to expand, the importance of zero-knowledge proofs is likely to increase. We expect to see more advanced and sophisticated ZKP systems developed and implemented in various blockchain applications.

Overall, the use of zero-knowledge proofs in blockchain technology has the potential to revolutionize the way we think about privacy and security in the digital world.

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