Low Space Complexity Multiplier for Even-Type Gaussian Normal Basis over GF(2m)

Gaussian normal basis in multiplier design perform excellent, matrix-vector decomposition is most important part in multiplication algorithm. In this paper, we proposed a symmetric matrix-vector product method, theoretical analysis shows that the proposed scheme is less space complexity comparing to the traditional TMVP approach. The main advantage of the proposed multiplier is can be designed and implementationin in a smaller size and we can reduce a large number of AND gates.