• One Face, One DID
  • A rapid and privacy-preserving solution to combat bot and sybil attacks.

  • What is zkMe DID?

    The "one face, one DID" concept is a powerful tool in the fight against bots and sybil attacks. By requiring users to verify their identity through facial recognition, zkMe ensures that each user has a unique DID. This makes it much more difficult for bad actors to create multiple accounts and manipulate the system.
    With zkMe, businesses can be confident that their interactions are with real people, and not bots or fake accounts.

The "one face, one DID" concept is a powerful tool in the fight against bots and sybil attacks. By requiring users to verify their identity through facial recognition, zkMe ensures that each user has a unique DID. This makes it much more difficult for bad actors to create multiple accounts and manipulate the system.
With zkMe, businesses can be confident that their interactions are with real people, and not bots or fake accounts.

Why choose zkMe DID solution?

  • Privacy first

    Protect user privacy with full homomorphic encryption.

  • Instant check

    Quickly verify accuracy and effectiveness.

  • Reusable

    One-time verification, repeatable use.

  • Build a more secure and trustworthy community

  • Prevent Abusive Behavior

    zkMe DID is a system that proves you are a real and unique person while fully protecting your privacy. At the same time, it can prevent sybil attacks on chains and communities.

  • Establish New Governance Models

    Using token-based voting can prevent Sybil attacks, but it can create non-democratic models and low community engagement. One Face, One DID system can help transition to a secure one person, one vote system.

  • Ensure Fair Reward Systems

    zkMe DID guarantees a fair and safe system by rewarding real community members which creates increased engagement and a healthier community.

How does it work?

  • Liveness check

  • Faceprint generation

  • Fully homomorphic encryption

  • Encrypted faceprint cross-check

  • zkMe DID creation

Fully Homomorphic Encryption to Protect Users' Privacy

  • Use homomorphic encryption technology to secure facial feature data.
  • Extract facial features through liveness verification technology and encrypt using homomorphic encryption.
  • Perform calculations on encrypted data to ensure sensitive data is not exposed in plaintext.
  • Save DID identifier and facial feature ciphertext in the database to complete registration if facial features are not registered.

zkMe DID use cases

  • Antispam

  • Fair
    Airdrops

  • Fair
    NFT mint

  • Fair
    Funding

  • Fair
    Voting

  • Quadratic
    Funding

  • Antispam

  • Fair
    Airdrops

  • Fair
    NFT mint

  • Fair
    Funding

  • Fair
    Voting

  • Quadratic
    Funding

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