BKC Oracle
  • About
    • About BKC Oracle
    • Connect with MetaMask
  • Features
    • Data feeds
    • Verifiable Random Function (VRF)
  • How to
    • Using Data Feed
    • Using VRF
  • Examples
    • Data Feed Consumer
    • VRF Consumer
  • Utilities
    • Contract Addresses
      • Bitkub Mainnet
      • Bitkub Testnet
    • Data Feed Proxy Contract Interface
      • AggregatorInterface’s Methods
      • AggregatorV3Interface’s Methods
    • Key Hash
  • Deprecated
    • What’s dashboard?
      • How to manage subscriptions?
      • How to add a new subscription?
      • How to convert KUB to KKUB?
    • Interface Requirement of a Consumer Contract
    • How to subscribe to data oracle?
      • Monthly subscription
      • Annual subscription
  • Links
    • Get KDEV
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  1. Features

Verifiable Random Function (VRF)

Introduction: Welcome to our Verifiable Random Function (VRF) service, a powerful cryptographic tool that provides secure and verifiable randomness for various applications. Whether you're involved in blockchain protocols, decentralized systems, or any other domain requiring unbiased and unpredictable randomness, our VRF solution offers a reliable way to generate and verify random outputs.

What is a VRF? A Verifiable Random Function (VRF) is a cryptographic construction that produces random-looking outputs while offering the ability to verify the authenticity of those outputs. It combines the properties of randomness, verifiability, pseudorandomness, and unpredictability. By leveraging VRFs, you can ensure that generated random data remains unbiased, tamper-proof, and publicly verifiable.

Key Features:

  1. Randomness: Our VRF service generates outputs that are indistinguishable from true randomness, providing a high level of unpredictability.

  2. Verifiability: With our VRF solution, anyone can easily verify the authenticity of generated random outputs by utilizing the associated public key. This enables transparent and trustless verification.

  3. Pseudorandomness: VRFs offer deterministic behavior, meaning that the same input will always produce the same output. This property ensures consistency and reproducibility when working with random data.

  4. Unpredictability: The unpredictable nature of VRFs ensures that it is computationally infeasible to predict the output without knowledge of the secret key, adding an additional layer of security.

Conclusion: Our Verifiable Random Function (VRF) service offers a reliable and efficient solution for generating and verifying secure randomness. By harnessing the power of VRFs, you can introduce fairness, transparency, and trust into your applications, ensuring the integrity of critical processes. Explore our VRF service today and experience the benefits of a robust and verifiable source of randomness.

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Last updated 1 year ago