Image Encryption Method Based on Image Dimension Transformation Using Chaotic Flow systems

• Atheer J. Mansoor
• Hikmat N. Abdullah
• Hadi T. Zeboon

Palabras clave: security, image encryption, image scrambling, chaotic sequences, pixels coordinate

Resumen

Image encryption today is divided into changing image pixels’ value or chang- ing image pixels’ coordinates. In this paper, an image encryption system based on changing both pixels’ value and position using one chaotic flow systems is proposed. At first, image dimension is changed form an M*N matrix into a vector of 1*(M*N), then Implement the random number generated from cha- os system to produce the final encrypted image. The system has been imple- mented on equal and non-equal dimension images and tested by using testing techniques:- correlation coefficient, DSF, ADC, PSNR, EQ ,ARE, MD, ID , measurement based on the value and position changing and entropy. Then the result is compared with the traditional scheme which uses ACM for scram- bling then any chaotic system for changing pixel’s value. The simulation results show that, keeping almost the same encryption results quality but with decreasing the required time for encryption and decryption.

Citas

Gao, T., & Chen, Z. (2008)). A new image encryption algorithm based on hyper-chaos. Physics Letters, Elsevier, 394–400.

Tang , Z., & Zhang, X. (2011). Secure Image Encryption without Size Limitation Using Arnold Transform and Random Strategies. JOURNAL OF MULTIMEDIA , 202-206.

Arnold Transform Based Image Scrambling Method. (2013). 3rd Inter- national Conference on Multimedia Technology (pp. 1309-1316). China: Atlantis Press.

Gaspard, P. (2005). R ̈ossler systems. Encyclopedia of Nonlinear Science, 808-811.

Gupta, P., Singh, S., & Mangal, I. (2014). Image Encryption Based On Arnold Cat Map and S-Box. International Journal of Advanced Research in Computer Science and Software Engineering, 807-812.

H.H. Nien, C. H. (2005). Digital color image encoding and decoding using a novel chaotic random generator. Chaos, Solitons and Fractals, Elsevier, 1070–1080.

Image Encryption Algorithm based on Chaotic Map Lattice and Arnold cat map for Secure Transmission. (March 2011). International Journal of Computer Sci ence and Technology IJCST, 132-135.

Jing-yu, P. (2013). Efficient Color Image Encryption and Decryption Al- gorithm. International Journal of Digital Content Technology and its Ap- plications(JDCTA), 129-136.

Jing-yu, P. (2013). Efficient Color Image Encryption and Decryption Al- gorithm. International Journal of Digital Content Technology and its Ap- plications(JDCTA), 7(6), 129-136.

Mansor, A. J., Abdullah, H. N., & Zeboon, H. T. (2017). Robust Encryp- tion System Based on Novel Chaotic Sequence. Research Journal of Ap- plied Sciences, Engineering and Technology, 14(1), 48-55.

Mao, Y., Cao, L., & Liu, W. (n.d.). Design and FPGA Implementation of a Pseudo-Random Bit Sequence Generator Using Spatiotemporal Chaos.

Merah, L., Ali-Pacha, A., Said, N. H., & Mamat, M. (2013,). Design and FPGA Implementation of Lorenz Chaotic System for Information Security Issues. Applied Mathematical Sciences, 237 - 246.

Mirghadri, A. J. (2010). A New Approach to Measure Quality of Image Encryption. (IJCNS) International Journal of Computer and Network Se- curity, 38-43.

Peterson, G. (1997). Arnold’s Cat Map.

Prasad, M., & Sudha, K. (2011). Chaos Image Encryption using Pixel shuf- fling. Computer Science & Information Technology (CS & IT), 169–179. Willsey, M., Cuomoy, K., & Oppenheim, A. (2010). Selecting the Lorenz Parameters for Wideband Radar Waveform Generation. INTERNATION- AL JOURNAL OF BIFURCATION AND CHAOS, 1-12.

Zhu Liehuang, L. W. (2006). A Novel Image Scrambling Algorithm for Digital Watermarking Based on Chaotic Sequences. International Journal of Computer Science and Network Security (IJCSNS), 6(8B), 125-130.