🤖 AI Summary
This work addresses the long-standing challenge of identifying efficiently solvable instances of the Linear Equivalence Problem (LEP), which underpins the security of several post-quantum cryptographic schemes. For the first time, the study systematically exploits algebraic structural weaknesses in LEP by introducing a novel approach that integrates power codes, Frobenius automorphisms, and Hermitian kernels. This framework generalizes Schur product–based techniques to arbitrary linear equivalence settings. By analyzing the coefficient structure within multiplicative subgroups of finite fields, the authors identify multiple new families of tractable LEP instances. Under these conditions, they achieve a significantly more efficient reduction from LEP to the Permutation Equivalence Problem (PEP), thereby substantially expanding the known solvable boundary of LEP.
📝 Abstract
Given two linear codes, the Linear Equivalence Problem (LEP) asks to find (if it exists) a linear isometry between them; as a special case, we have the Permutation Equivalence Problem (PEP), in which isometries must be permutations. LEP and PEP have recently gained renewed interest as the security foundations for several post-quantum schemes, including LESS. A recent paper has introduced the use of the Schur product to solve PEP, identifying many new easy-to-solve instances. In this paper, we extend this result to LEP. In particular, we generalize the approach and rely on the more general notion of power codes. Combining it with Frobenius automorphisms and Hermitian hulls, we identify many classes of easy LEP instances. To the best of our knowledge, this is the first work exploiting algebraic weaknesses for LEP. Finally we show an improved reduction to PEP whenever the coefficients of the monomial matrix are in a subgroup of the multiplicative group of the finite field.