Complexity Determination of Stream Cipher Sequence based on Discrete-Time Signal Transformation
Sattar B. Sadkhan · 2020
Recently, stream cipher systems have played a big role, especially in computer networks. Stream cipher systems depend on Pseudo-Random (P.R.) binary key sequences which are mixed with the plaintexts using addition with modulo two to produce the ciphertexts. The PR key sequences are characterized by three properties which are complexity, period, and randomness. In order to determine the Complexity degree of these Pseudo-Random sequences, many methods and techniques were used, like statistical method, Berlekamp-Massey method, information theory parameters method, and software computing techniques (Fuzzy logic, Neural Networks, Genetic Algorithms, and Adaptive Neural Fuzzy Inference System -ANFIS-). The main aim of this paper is to use a proposed method to determine the complexity degree of these Pseudo-Random sequences using one of the properties of the Z-transform, which is periodic sequence property. This proposed method enables the researchers to compute the complexity degree of any periodic sequence produced from linear or nonlinear generators, and accurate results are obtained. The steps of the proposed procedure are given, two different examples are illustrated one of them for a P.R. sequence over G.F. (2), and the second example for P.R. sequence over G.F. (5).