research/mimc_stark
Vitalik Buterin 5f762aee81 Cut down to 2 non-trivial FFTs 2018-07-11 11:46:21 -04:00
..
README.md More efficiency 2018-07-04 05:33:51 -04:00
better_lagrange.py Improved efficiency a bunch and added boundary checks 2018-07-10 15:45:12 -04:00
compression.py Reorganized the code somewhat 2018-07-10 08:49:25 -04:00
fft.py More efficiency 2018-07-04 05:33:51 -04:00
fri.py Cut down to 2 non-trivial FFTs 2018-07-11 11:46:21 -04:00
merkle_tree.py Reorganized the code somewhat 2018-07-10 08:49:25 -04:00
mimc_stark.py Cut down to 2 non-trivial FFTs 2018-07-11 11:46:21 -04:00
poly_utils.py Cut down to 2 non-trivial FFTs 2018-07-11 11:46:21 -04:00
test.py Cut down to 2 non-trivial FFTs 2018-07-11 11:46:21 -04:00
utils.py Cut down to 2 non-trivial FFTs 2018-07-11 11:46:21 -04:00

README.md

Disclaimer

DO NOT USE FOR ANYTHING IN REAL LIFE. DO NOT ASSUME THE PROTOCOL DESCRIBED HERE IS SOUND. TALK TO A SPECIALIST IF YOU'RE LOOKING TO USE STARKS IN YOUR APPLICATION.

What is this?

This is a very basic implementation of a STARK on a MIMC computation that is probably (ie. definitely) broken in a few places but is intended as a proof of concept to show the rough level of complexity that is involved in implementing a simple STARK. A STARK is a really cool proof-of-computation scheme that allows you to create an efficiently verifiable proof that some computation was executed correctly; the verification time only rises logarithmically with the computation time, and that relies only on hashes and information theory for security.

The STARKs are done over a finite field chosen to have 2**32'th roots of unity (to facilitate STARKs), and NOT have 3rd roots of unity (to facilitate MIMC). The MIMC permutation in general takes the form:

                       k_1                     k_2
                        |                       |
                        v                       v
x0 ---> (x->x**3) ---> xor ---> (x->x**3) ---> xor --- ... ---> output

Where the k_i values are round constants. MIMC can be used as a building block in a hash function, or as a verifiable delay function; its simple arithmetic representation makes it ideal for use in STARKs, SNARKs, MPC and other "cryptography over general-purpose computation" schemes.

The MIMC round constants used here are successive powers of 9 mod 2**256 xored with 1, though could be set to anything. The computational trace is computed over successive powers of a 2**k'th root of unity. This allows the constraint checking polynomial to be C(P(x), P(r*x), K(x)) = P(r*x) - P(x)**3 - K(x).

For a description of how STARKs work, see:

For more discussion on MIMC, see:

How does the STARK scheme here work?

Here are the approximate steps in the code. Note that all arithmetic is done over the finite field of integers mod 2**256 - 2**32 * 351 + 1.

  1. Let P[0] equal the input, and P[i+1] = P[i]**3 + K[i], up to steps (where steps must be a power of 2)
  2. Construct a polynomial where P(subroot ^ i) = P[i] up to steps-1, where subroot is a steps'th root of unity (that is, subroot**steps = 1). Do the same with K.
  3. Construct the polynomial CP(x) = C(P(x), P(x * subroot), K(x)). Note that since P(x * subroot) = P(x) ^ 3 + K(x), CP(x) = 0 for any x inside the computation trace (that is, powers of subroot except the last).
  4. Construct the polynomial Z(x), which is the minimal polynomial that is 0 across the computation trace. Note that because Z is minimal, CP must be a multiple of Z.
  5. Construct D = CP / Z. Because CP is a multiple of Z, D must itself be a low-degree polynomial.
  6. Put D and P into Merkle trees.
  7. Construct L = D + k * x**steps * P, where k is selected based on the Merkle roots of D and P.
  8. Create an FRI proof that L is low-degree ((7) and (8) together are a clever way of making an aggregate low-degree proof of D and P)
  9. Create probabilistic checks, using the Merkle root of L as source data, to spot-check that D(x) * Z(x) actually equal C(P(x)).

The probabilistic checks and the FRI proof are themselves restricted to 2**precision'th roots of unity, where precision = 8 * steps (so we're FRI checking that the degree of L, which equals twice the degree of P, is at most 1/4 the theoretical maximum).