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TitleEfficient Algorithms for Solving Overdefined Systems of Multivariate Polynomial Equations
Author(s) Nicolas T. Courtois, Alexander Klimov, Jacques Patarin, Adi Shamir
TypeBook, Chapter in Book, Conference Proceeding
AbstractThe security of many recently proposed cryptosystems is based on the difficulty of solving large systems of quadratic multivariate polynomial equations. This problem is NP-hard over any field. When the number of equations m is the same as the number of unknowns n the best known algorithms are exhaustive search for small fields, and a Gröbner base algorithm for large fields. Gröbner base algorithms have large exponential complexity and cannot solve in practice systems with n ≥ 15. Kipnis and Shamir [9] have recently introduced a new algorithm called relinearization . The exact complexity of this algorithm is not known, but for sufficiently overdefined systems it was expected to run in polynomial time. In this paper we analyze the theoretical and practical aspects of relinearization. We ran a large number of experiments for various values of n and m, and analysed which systems of equations were actually solvable. We show that many of the equations generated by relinearization are linearly dependent, and thus relinearization is less efficient that one could expect. We then develop an improved algorithm called XL which is both simpler and more powerful than relinearization. For all 0 < ε ≤ 1/2, and m ≥ εn 2, XL and relinearization are expected to run in polynomial time of approximately $$n^{\mathcal{O}(1/\sqrt \varepsilon )} $$ . Moreover, we provide strong evidence that relinearization and XL can solve randomly generated systems of polynomial equations in subexponential time when m exceeds n by a number that increases slowly with n.
URL http://dx.doi.org/10.1007/3-540-45539-6_27
SeriesLecture Notes in Computer Science
PublisherSpringer Berlin / Heidelberg
EditorPreneel, Bart
Translation No
Refereed No
BookAdvances in Cryptology EUROCRYPT 2000