orochi logo
|
Pricing
Pricing
orochi logo

Be the first to know about the latest updates and launches.

Star us on Github

Follow us on

  • Product
  • zkDatabase
  • Orocle
  • Orand
  • zkMemory
  • zkDA Layer (TBA)
  • Pricing
  • Developers
  • Documents
  • RAMenPaSTA
  • Research
  • Support Center
  • npm Packages
  • Resources
  • Blog
  • Brand Assets
  • Case Studies (TBA)
  • Ecosystem
  • ONPlay
  • $ON Token
  • Become a Partner
  • Discover
  • About us
  • Contact Us
  • Orochian Onboarding

Privacy Policy

|

Terms of Service

|

© 2025 Orochi Network. All rights reserved.

f54ac39
Blog
>
Verifiable Random Function & Oracle

Top 5 Implementations of Verifiable Random Functions

November 4, 2025

5 mins read

In this article, we will explore the top 5 implementations of VRFs and their importance in cryptography.

345838873_463310082661159_9003147099585340360_n.jpg

I. Introduction

Verifiable Random Functions (VRFs) have emerged as a prominent cryptographic technique due to their unique capability to generate random values that can be verified without disclosing the original seed value. This approach ensures both randomness and confidentiality in cryptographic operations. In this article, we will explore the top 5 implementations of VRFs and their importance in cryptography.

II. What are Verifiable Random Functions (VRFs)?

A verifiable random function is a type of cryptographic function that computes a set of inputs into a pseudorandom output and provides verifiable evidence of authenticity. A public/private key pair (sometimes referred to as a verification key and secret key) and a seed are frequently used as inputs for a VRF. A seed is chosen, and a public/private key pair is produced. These inputs are sent to the VRF, which generates a random number using the private key and the seed. Based on that, the VRF then generates a random number and a proof. Importantly, the creation of a proof makes the function verifiable while maintaining the number's randomness by keeping the secret key hidden. Mathematically explained, given the input x, the holder of the secret key SK** can determine  (y,y)= FSK(x)  where y is the pseudorandom output and is the proof of y. Anyone can verify that the value of y was indeed computed correctly by using the proof and the public key PK, but this information cannot be used to find the secret key SK **by this formula PK= GSK
To learn more about VRFs and their applications to the blockchain industry, we recommend you to check out our article on the topic: Verifiable Random Function (VRF) & Applications in Blockchain - Orochi Network. 

III top 5 implementations of VRF

  • RSA Accumulators
RSA Accumulators are a data structure that can accumulate data in a way that allows for efficient verification of membership. They can be used as a VRF implementation by constructing the accumulator using the RSA trapdoor function. The RSA accumulator VRF generates a random value based on a secret input value that can be verified by anyone using the accumulator. This makes RSA accumulators a powerful tool for generating random values in a secure and efficient manner.
RSA Accumulators can be used in blockchain systems to generate random values for the selection of validators and distribution of rewards. It can also be used to generate nonces in digital signatures to prevent replay attacks.
  • EdDSA
EdDSA (Edwards-curve Digital Signature Algorithm) is a modern digital signature scheme based on elliptic curve cryptography. EdDSA can also be used as a VRF implementation. The algorithm generates a random value as an input to generate a signature that can be verified by anyone using the public key. EdDSA's VRF implementation is secure and efficient, making it a popular choice for generating random values.
For instance, EdDSA can be used in distributed ledger technologies to generate random numbers for sharding, where nodes are partitioned into different subgroups to improve scalability.
  • BLS12-381
BLS12-381 is an elliptic curve that can be used to create digital signatures and perform cryptographic operations. It can also be used as a VRF implementation. The BLS12-381 VRF generates a random value based on a secret input, and the output can be verified using the public key. BLS12-381 is known for its fast performance and high level of security, making it an excellent choice for VRF implementations.
BLS12-381 implementation is in the privacy-focused cryptocurrency Zcash, which uses the BLS12-381 curve for generating random values for the selection of validators and the creation of transactions.
  • Schnorr Signatures
Schnorr Signatures is a digital signature scheme based on the discrete logarithm problem. It can also be used as a VRF implementation. The algorithm generates a random value based on a secret input, and the output can be verified using the public key. Schnorr Signatures VRF is highly secure and efficient, making it a popular choice for generating random values.
Schnorr Signatures can be used in decentralized finance (DeFi) platforms for generating random values to ensure fairness in the selection of validators and the distribution of rewards.
  • ECDSA
ECDSA (Elliptic Curve Digital Signature Algorithm) is a popular digital signature scheme widely used in cryptography. It can also be used as a VRF implementation. The algorithm generates a random value based on a secret input, and the output can be verified using the public key. ECDSA VRF is highly secure and efficient, making it a popular choice for generating random values.
An example of ECDSA implementation is in the Bitcoin protocol, where it is used to generate random numbers for creating transactions and blocks.

IV. Conclusion

In conclusion, VRFs are an essential tool in modern cryptography. In this article, we explored the top 5 implementations of VRFs, including RSA accumulators, EdDSA, BLS12-381, Schnorr Signatures, and ECDSA. These VRF implementations provide an efficient and secure way to generate random values, making them an essential part of many cryptographic protocols. As new cryptographic algorithms are developed, we can expect to see even more powerful VRF implementations emerge in the future.

Share via

facebook-icontelegram-icon
I. IntroductionII. What are Verifiable Random Functions (VRFs)?III top 5 implementations of VRFIV. Conclusion
Experience verifiable data in action - Join the zkDatabase live demo!
Book a Demo

More posts

blog card

Data Provenance and Integrity in Tokenized Markets: Why Privacy-Preserving, Verifiable Inputs Decide RWA Success in 2025–2026

Research

blog card

The Evolution of Databases: From SQL to zkDatabase

Research

blog card

Low-Cost ZK Rollups | How Orochi Optimizes Data Proof Scalability ?

Research

blog card

What is Orochi Network ?

Orochi Essentials

Top Post

blog card

$ON AIRDROP - CHECK YOUR ALLOCATION

Orochi Foundation

Orochi Essentials

blog card

Orochi Network × zkPass | Partnership Announcement

Partnership

Related to this category

blog card

Verifiable Random Function (VRF) & Applications in Blockchain

Verifiable Random Function & Oracle

blog card

The importance of Randomness to Blockchains and Web3

Verifiable Random Function & Oracle

blog card

How Verifiable Random Functions Are Revolutionizing Online Gaming and Gambling

Verifiable Random Function & Oracle

blog card

ECVRF: The Next Generation of Cryptographic Randomness

Verifiable Random Function & Oracle

blog card

Impact of Verifiable Random Functions on Cryptography and Cybersecurity

Verifiable Random Function & Oracle

blog card

Understanding Verifiable Random Functions (VRFs) and Their Role in DeFi

Verifiable Random Function & Oracle