📡 ZkWave: Transforming Voice into Secure Proofs 🎤🔐

🚀 Overview

ZkWave is an innovative project that combines audio signal processing, polynomial mathematics, and zero-knowledge cryptography. With ZkWave, we securely convert voice data into mathematical polynomials and leverage Zero-Knowledge Proofs (ZKP) to verify voice-based information without exposing sensitive data.

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💡 Features

• 🎧 Voice-to-Polynomial Transformation
  Transform audio signals into polynomials for efficient compression, encryption, and secure representation.

• 🔒 Privacy-Preserving Voice Authentication
  Authenticate users through voice securely using zero-knowledge cryptography.

• 🛡️ Zero-Knowledge Encryption
  Enable secure and private proof generation using zk-SNARKs or zk-STARKs.

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📚 How It Works

1. Voice Signal Processing

   • Record and digitize voice input (WAV format).
   • Preprocess the audio for noise reduction and normalization.

2. Polynomial Representation

   • Model voice signals as mathematical polynomials using least squares approximation or spline fitting.
   • Compress voice features into polynomial coefficients.

3. Zero-Knowledge Proofs

   • Generate ZKPs for the polynomial representation using Circom and snarkjs.
   • Verify proofs without revealing the underlying voice data.

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🛠️ Tech Stack

• Programming Language: Rust 🦀
• Cryptographic Framework: Circom, snarkjs 🔐
• Audio Processing: Rust's wav and ndarray crates
• Blockchain Integration (Optional): zkSync for decentralized verification

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🌐 Real-World Use Cases

1. Voice Authentication
   Verify users’ identities through private voice-based authentication.

2. Secure Communication
   Enable provably secure and private voice transmissions.

3. Privacy-Preserving Voice Analytics
   Analyze voice features without exposing sensitive data.

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📋 Project Completion Checklist

1. Voice Processing Implementation

• Write Rust code to load and process WAV audio files.
• Implement a function to extract audio samples from the WAV file.
• Normalize and fit the audio samples to a polynomial using regression.
• Serialize the polynomial coefficients and evaluation data into a JSON input format for Circom.

2. Circom Circuit Development

• Design a Circom circuit for verifying the polynomial evaluation (VerifyPolynomial).
• Add debug signals to the circuit for easier debugging and validation.
• Compile the Circom circuit into r1cs, wasm, and other required formats.
• Test the circuit using valid JSON inputs to ensure correctness.
• Optimize the circuit for performance and size.

3. Zero-Knowledge Proof Integration

• Set up the Groth16 proving system using snarkjs.
• Generate the trusted setup phase (.zkey file) using a precomputed PTAU.
• Create the proof and verify it locally with snarkjs.
• Export the proof and verification key for use in the mini app.

4. Private TON Mini App

• Design and implement the private TON mini app interface.
• Integrate the zero-knowledge proof verification in the mini app.
• Implement secure storage and handling for sensitive user data.

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🚀 Future Enhancements (Optional)

• Extend support for additional audio file formats (e.g., MP3, FLAC).
• Implement more efficient polynomial fitting algorithms.
• Explore alternative zero-knowledge proof systems for optimization.

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🤝 Contributing

We welcome contributions! Whether it’s reporting bugs, suggesting features, or submitting pull requests, check out our Contributing Guide.

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📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

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🎉 Join the Wave!

Be part of the privacy revolution with ZkWave. If you have ideas, feedback, or want to collaborate, feel free to open an issue or contact us!