Algorithms to Solve Massively Under-Defined Systems of Multivariate Quadratic Equations

摘要

It is well known that the problem to solve a set of randomly chosen multivariate quadratic equations over a finite field is NP-hard. However, when the number of variables is much larger than the number of equations, it is not necessarily difficult to solve equations. In fact, when n ≥ m(m + 1) (n, m are the numbers of variables and equations respectively) and the field is of even characteristic, there is an algorithm to find one of solutions of equations in polynomial time (see Kipnis et al., Eurocrypt'99 and also Courtois et al., PKC'02). In the present paper, we propose two new algorithms to find one of solutions of quadratic equations; one is for the case of n ≥ (about)m~2 - 2m~(3/2) + 2m and the other is for the case of n > m(m + l)/2 + 1. The first one finds one of solutions of equations over any finite field in polynomial time, and the second does with O(2~m) or O(3~m) operations. As an application, we also propose an attack to UOV with the parameters given in 2003.