 Module learning with errors

Module learning with errors is a structured version of learning with errors in which matrix entries and secret components are elements of a specified polynomial ring. A typical relation isHere $A$ is a public $k\times k$ matrix of ring elements, while $s$ and $e$ have sampled small coefficients. Multiplication combines polynomial multiplication with reduction by the defining polynomial and coefficient modulus.

A ring element packs $n$ coefficients, giving structured linear operations without storing an arbitrary dense matrix of all scalar coefficients. This saves space and computation, while introducing an algebraic structure that the security assumption must cover. CRYSTALS-Kyber uses module-LWE, and ML-KEM standardizes a related encapsulation construction. This is a conditional hardness basis, not a proof that every choice of ring and parameters is secure.^[ref]