Development of micro computer based mobile random number generator with an encryption application

In this study, an equation is derived by changing the parameter values of a chaotic system in the literature and analyzing its chaotic behavior. In the analysis of chaotic behaviors, chaotic system analyses such as phase portraits, sensitivity to initial conditions, Lyapunov exponential spectrum and dimension analysis, bifurcation diagram with Matlab® software were investigated. The derived equations were embedded into a mobile random number generator (RNG). RNG was developed on the Raspberry Pi 3 Model B microcomputer. It has been shown that the obtained random numbers can be securely used in encryption applications by successfully passing the statistical tests NIST 800-22, FIPS 140-1 and ENT. An image encryption application with the generated random numbers was implemented on the Raspberry Pi 3 Model B microcomputer. Finally, the encrypted image was subjected to security tests such as histogram analysis, correlation and entropy coefficients, correlation card, NPCR, UACI utilizing MATLAB software. The performance and reliability of the encryption algorithm were also measured. This paper improves the current state of art as it implements chaotic random number generation algorithm in a small footprint micro computer. •A 3D nonlinear equation is derived by changing the parameter values of a chaotic system in the literature and analyzing its chaotic behavior. Some dynamical analysis such as phase portraits, sensitivity to initial conditions, Lyapunov exponential spectrum and dimension analysis, bifurcation diagram with Matlab® software were investigated.•The derived equations were embedded into a mobile random number generator (RNG). RNG was developed on the Raspberry Pi 3 Model B microcomputer.•It has been shown that the obtained random numbers can be securely used in encryption applications by successfully passing the statistical tests NIST 800-22 and FIPS 140-1.•An image encryption application with the generated random numbers was implemented on the Raspberry Pi 3 Model B microcomputer. The encrypted image was subjected to some security tests.