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An RSA accumulator is an authenticated set built from cryptographic assumptions in hidden-order groups such as $\mathbb{Z}_N^*$. RSA accumulators enable a prover, who stores the full set, to convince any verifier, who only stores a succinct digest of the set, of various set relations such as (non)membership, subset or disjointness. For example, ...

A vector commitment (VC) scheme allows a prover with access to a vector $\mathbf{v} = [ v_1, \dots, v_n ]$ to convince any verifier that position $i$ in $\mathbf{v}$ stores $v_i$ for any index $i\in[n]$. Importantly, verifers only store a succinct digest of the vector (e.g., a 32-byte hash) rather than the full vector $\mathbf{v}$.

Equations of the form $\sum_i a_i x_i = 0$ where the $x_i$’s are integer unknowns are called linear Diophantine equations. Their integer solutions can be computed using greatest common denominator (GCD) tricks. In this post, we go over a few basic types of such equations and their integer solutions.

In this post, we summarize some of the cryptographic hardness assumptions used in hidden-order groups.

Kate, Zaverucha and Goldberg introduced a constant-sized polynomial commitment scheme in 20101. We refer to this scheme as KZG and quickly introduce it below. Prerequisites: Cyclic groups of prime order and finite fields $\Zp$ Pairings (or bilinear maps) Polynomials Trusted setup To commit to degree $\le \ell$ polynomials, need $\ell...

tl;dr: We build a vector commitment (VC) scheme from KZG commitments to Lagrange polynomials that has (1) constant-sized, aggregatable proofs, which can all be precomputed in $O(n\log{n})$ time, and (2) linear public parameters, which can be derived from any “powers-of-tau” CRS in $O(n\log{n})$ time. Importantly, the auxiliary information needed...

tl;dr: We give on overview of bilinear accumulators, a more communication-efficient alternative to Merkle Hash Trees (MHTs) that comes at an increase in computation. Put simply, bilinear accumulators are commitments to sets with constant-sized (non)membership proofs. For more details, see this full post on Decentralized Thoughts.

These are some notes on how to efficiently multiply a Toeplitz matrix by a vector. I was writing these for myself while implementing the new amortized KZG proofs by Feist and Khovratovich, but I thought they might be useful for you too.