A Sticker-Based Model Using DNA Computing for Generating Real Random Numbers

Abstract

Real random values have wide range of application in different field of computer science such as cryptography, network security and communication, computer simulation, statistical sampling, etc. In purpose of generating real random values, need for a natural noisy source refers to the main challenge where a source of noise may be reliable for using in random number generator if and only if be derived from physical environment. In this work, we address this requirement by using DNA computing concepts where the molecular motion behavior of DNA molecular provides a pure source of physical noise that may be used for generating high quality real random values. Since one of the main factor for evaluating quality of real random values refer to expectation for generating approximately same amount of 0s and 1s, in this article we model a DNA-based random number generator in sticker mode with ability of generating equal numbers of 0 and 1. After using molecular motion behavior of DNA molecular as the natural source of noise into the proposed DNA-based random number generator, the generated value were subjected to frequency, run, and serial tests which are proposed by National Institute of Standards and Technology (NIST) for randomness evaluation. Obtained result from this evaluation shows that beside the achieving high scores in run and serial tests, the values generated by our DNA-based random number generator pass frequency test with 100% success.