Dynamic Data Experiments

This is a prototype implementation of the proposed Codex storage proofs for dynamic data.

Erasure Coding & Commitment

• Organize data as byte Matrix with k rows and m columns
• Convert the byte Matrix to Field Matrix with k rows and m columns
• Each cell in the Field matrix is "fat" (fat cell = z field elements) -> end up with (k/z)*m Matrix
• Erasure code the columns -> end up with n*m Matrix
• Commit to each "fat" cell in each row independently with KZG
• Commit to each row independently with KZG
• Build a Merkle tree with the KZG commitments

Note: in the above I switched the directions of the encoding and commitment (opposite of the proposal) just because it was easier to implement but basically it is same thing.

Sampling

• Select a set of columns randomly
• Generate a KZG evaluation proof at random point for each column
• Aggregate the KZG evaluation proofs

Updating the Data

• Select a row (or multiple)
• Query the original row
• Update the cells in that row
• Erasure code the updated row

Updating the Commitments

• Query the old row and receive the new row
• Compute the delta = r' - r
• Query the old the "fat" cell commitment and compute the new one
• Compute the delta_comm = fat_comm' - fat_comm
• Compute the new row commitment row_comm' = row_comm + delta

Prove Data & Commitment Update

• TODO...

TODO:

• Clean up and optimize
• Simulate interactions between Client (Data Owner) and SP (Storage Provider)
• Add details and write-up & experimentation/benchmark results

WARNING: This repository contains work-in-progress prototypes, and has not received careful code review. It is NOT ready for production use.