International Association
for Cryptologic Research

Recently, there has been a lot of interest in improving the understanding of the practical hardness of the 3-Tensor Isomorphism (3-TI) problem, which, given two 3-tensors, asks for an isometry between the two. The current state-of-the-art for solving this problem is the algebraic algorithm of Ran et al. '23 and the graph-theoretic algorithm of Narayanan et al. '24 that have both slightly reduced the security of the signature schemes MEDS and ALTEQ, based on variants of the 3-TI problem (Matrix Code Equivalence (MCE) and Alternating Trilinear Form Equivalence (ATFE) respectively). In this paper, we propose a new combined technique for solving the 3-TI problem. Our algorithm, as typically done in graph-based algorithms, looks for an invariant in the graphs of the isomorphic tensors that can be used to recover the secret isometry. However, contrary to usual combinatorial approaches, our approach is purely algebraic. We model the invariant as a system of non-linear equations and solve it. Using this modelling we are able to find very rare invariant objects in the graphs of the tensors — cycles of length 3 (triangles) — that exist with probability approximately 1/q. For solving the system of non-linear equations we use Gröbner-basis techniques adapted to tri-graded polynomial rings. We analyze the algorithm theoretically, and we provide lower and upper bounds on its complexity. We further provide experimental support for our complexity claims. Finally, we describe two dedicated versions of our algorithm tailored to the specifics of the MCE and the ATFE problems. The implications of our algorithm are improved cryptanalysis of both MEDS and ALTEQ for the cases when a triangle exists, i.e. in approximately 1/q of the cases. While for MEDS, we only marginally reduce the security compared to previous work, for ALTEQ our results are much more significant with at least 60 bits improvement compared to previous work for all security levels. For Level I parameters, our attack is practical, and we are able to recover the secret key in only 1501 seconds. The code is available for testing and verification of our results.