Randomness properties of sequence generated using logistic map with novel permutation and substitution techniques

In this paper, a design of a chaos-based keystream generator (KSG) using a novel permutation technique with various two-dimensional patterns and a substitution technique with Z4 mapping is proposed. Initially, a chaotic function such as a logistic map is used to generate a pseudo-random number. Then these numbers are converted into binary sequences using binary mapping. In order to achieve statistical properties of the resultant binary sequences, a novel method of KSG is developed by considering parameters such as initial value “x0”, system parameter “r”, novel permutation techniques defined by 2-dimensional patterns, and substitution technique defined over Z4 transformation. The binary sequences so obtained are subjected to randomness tests by applying the National Institute of Standards and Technology (NIST) SP-800-22 (Revision 1a) test suite for investigation of its randomness properties to obtain suitable sequences which can be used as a key for cryptographic applications. From the results obtained, it is found that the binary sequences exhibit better randomness properties as per the cryptographic requirements

Pseudo Random Binary Sequences Obtained Using Novel Chaos Based Key Stream Generator and their Auto-correlation Properties

In this paper, psuedo random binary sequences are generated from the “Chaos Based Key Stream Generator- using novel Permutation technique with two dimensional patterns and substitution technique with Z4 mapping” and investigation of auto correlation property for the generated seuwnces is presented. Initially a chaotic function, considering Logistic map is used to generate a Pseudo Random Numbers (PRNs). Then these numbers are converted into binary sequences using binary mapping. These sequences are further modified by novel permutation techniques defined using 2-Dimensional patterns, and substitution technique defined over Z4 transformation in order to improve their statistical properties. The resulting sequences are investigated for auto correlation properties using Normalized Hamming Auto Correlation function. The purpose of this work is to assessing the quality of sequences of uniformly distributed pseudorandom numbers from the proposed generator. It is found that, generated sequences exhibit good auto-correlation property which is suitable for key sequence or secret key for cryptographic applications