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Krazy-G: KZG Commitments and Rust

CryptographyEngineering

At the start of this year I undertook a Rust implementation of the KZG polynomial commitment scheme. The dual goals were mastering Rust and refreshing my research engineering capabilities.

The implementation drew primarily from a fantastic blog by Dankrad Feist explaining the scheme step-by-step, supplemented by the original academic paper for structural guidance.

The Power of KZG

The scheme's remarkable efficiency cannot be overstated: proving polynomial evaluations at specific points requires sharing only one group element—48 bytes for BLS12_381 curves.

Think about that for a moment: you can prove that a chosen polynomial of any degree, when evaluated at a chosen point, gives a certain value, with only a single group element shared between the parties.

Using Lagrange Interpolation enables proving multiple point evaluations with the same single-element proof. This is particularly powerful for applications in zero-knowledge proofs and blockchain rollups.

Learning Rust Journey

Beginning in early 2022, I pursued structured learning through:

  • The Rust Book
  • Rust by Example
  • Rustlings exercises
  • Exercism challenges

However, these foundational resources proved insufficient without a substantial project. Reading about ownership and borrowing is one thing; wrestling with the borrow checker on real code is another entirely.

Traits and Abstraction

Understanding traits benefited from comparing them to Go interfaces, despite their differences. This connected nicely to cryptographic scheme definitions requiring specific algorithm implementations.

In cryptography, we often define schemes abstractly—specifying required algorithms like Keygen, Sign, and Verify—while implementations vary. Rust traits capture this pattern elegantly.

Memory Management

The ownership model and borrow checker initially posed significant challenges. I found myself fighting the compiler more than writing code.

The breakthrough came from revisiting the Rust Book's ownership chapter after gaining practical experience. Suddenly, concepts that seemed abstract clicked into place. The distinction between str and String types became clear, as did when to use references versus owned values.

Results

Successful end-to-end testing validated the implementation, yielding comprehensive understanding of:

  • Rust's ownership model and type system
  • Elliptic curve pairings and BLS12_381
  • KZG's growing adoption in zero-knowledge and rollup technologies

The project confirmed what I suspected: the best way to learn a language is to build something meaningful with it.