Digital Communication Based on Image Security using Grasshopper Optimization and Chaotic Map

Document Type : Original Article

Authors

Electronic and Control Engineering Techniques Department, Technical Engineering College – Kirkuk, Northern Technical University, Iraq

Abstract

Encryption is very important to protect sensitive data, especially images, from any illegal access and infringement. This research is presented to provide an image encryption optimization method for communication based on image security. This method uses the grasshopper optimization algorithm to perform optimal encryption and irregular logical mapping. Initially, this approach creates multiple encrypted images and a chaotic map, in which the session key for the initial conditions of the map depends on a simple suspended image. After that, the encrypted images work as an initial and particles set for optimization through the grasshopper optimization algorithm. The optimized encoded image with the correlation coefficient of the continuous pixels is expressed as a function of proportion. The results from Matlab simulation of the proposed encoding method show that the encrypted images are the same, and the adjacent pixels are highly correlated with other outstanding encoding rows, such as planar histogram entropy and effective pixel rate of change average correction strength.

Keywords

Main Subjects


  1. Nickel, S., Karimi, H. and Bashiri, M., "Capacitated single allocation p-hub covering problem in multi-modal network using tabu search", International Journal of Engineering, Transactions C: Aspects, Vol. 29, No. 6, (2016), 797-808. doi: 10.5829/idosi.ije.2016.29.06c.09.
  2. Su, Z., Zhang, G. and Jiang, J., "Multimedia security: A survey of chaos-based encryption technology", Multimedia-A Multidisciplinary Approach to Complex Issues, (2012). doi: 10.5772/36036
  3. Norouzi, B., Seyedzadeh, S.M., Mirzakuchaki, S. and Mosavi, M.R., "A novel image encryption based on hash function with only two-round diffusion process", Multimedia Systems, Vol. 20, No. 1, (2014), 45-64. doi: 10.1007/s00530-013-0314-4
  4. Furht, B. and Kirovski, D., "Multimedia security handbook, CRC press (2004).
  5. Wu, Y., Zhou, Y., Noonan, J.P. and Agaian, S., "Design of image cipher using latin squares", Information Sciences, Vol. 264, (2014), 317-339. doi: 10.1016/j.ins.2013.11.027.
  6. Hua, Z. and Zhou, Y., "Image encryption using 2d logistic-adjusted-sine map", Information Sciences, Vol. 339, (2016), 237-253. doi: 10.1016/j.ins.2016.01.017.
  7. Hassan, M.A.S. and Abuhaiba, I.S.I., "Image encryption using differential evolution approach in frequency domain," arXiv preprint arXiv:1103.5783,  (2011). doi: 10.48550/arXiv.1103.5783.
  8. Schneier, B., "Applied cryptography: Protocols, algorithms, and source code in c, john wiley & sons, (2007).
  9. Ye, R., Zeng, S., Lun, P., Ma, J. and Lai, C., "An image encryption scheme based on bit circular shift and bi-directional diffusion", Int J Inform Technol Comput Sci (IJITCS), Vol. 6, No. 1, (2014), 82-92. doi: 10.5815/ijitcs.2014.01.10.
  10. Enayatifar, R., Abdullah, A.H. and Lee, M., "A weighted discrete imperialist competitive algorithm (wdica) combined with chaotic map for image encryption", Optics and Lasers in Engineering, Vol. 51, No. 9, (2013), 1066-1077. doi: 10.1016/j.optlaseng.2013.03.010.
  11. Sabarinath, R., Jegadeesan, S. and Venkatalakshmi, K., "Image encryption using modified particle swarm optimization", IJRCCT, Vol. 3, No. 2, (2014), 241-246. doi: 10.1007/s41870-018-0099-y
  12. Naskar, P.K., Chaudhuri, A. and Chaudhuri, A., "A secure symmetric image encryption based on linear geometry", in 2014 Applications and Innovations in Mobile Computing (AIMoC), IEEE., (2014), 67-74.
  13. Ravichandran, D., Praveenkumar, P., Rayappan, J.B.B. and Amirtharajan, R., "Chaos based crossover and mutation for securing dicom image", Computers in Biology and Medicine, Vol. 72, (2016), 170-184. doi: 10.1016/j.compbiomed.2016.03.020‏
  14. Talarposhti, K.M. and Jamei, M.K., "A secure image encryption method based on dynamic harmony search (dhs) combined with chaotic map", Optics and Lasers in Engineering, Vol. 81, (2016), 21-34. doi: 10.1016/j.optlaseng.2016.01.006.
  15. Adleman, L.M., "Molecular computation of solutions to combinatorial problems", Science, Vol. 266, No. 5187, (1994), 1021-1024. doi: 10.1126/science.7973651.
  16. Zhang, X., Zhou, Z. and Niu, Y., "An image encryption method based on the feistel network and dynamic DNA encoding", IEEE Photonics Journal, Vol. 10, No. 4, (2018), 1-14.
  17. Zhang, J., Fang, D. and Ren, H., "Image encryption algorithm based on DNA encoding and chaotic maps", Mathematical Problems in Engineering, Vol. 2014, (2014). doi: 10.1155/2014/917147.
  18. Özkaynak, F. and Yavuz, S., "Analysis and improvement of a novel image fusion encryption algorithm based on DNA sequence operation and hyper-chaotic system", Nonlinear Dynamics, Vol. 78, No. 2, (2014), 1311-1320. doi: 10.1007/s11071-014-1517-8.
  19. Shiu, H.-J., Ng, K.-L., Fang, J.-F., Lee, R.C. and Huang, C.-H., "Data hiding methods based upon DNA sequences", Information Sciences, Vol. 180, No. 11, (2010), 2196-2208. doi: 10.1016/j.ins.2010.01.030
  20. Ravichandran, D., Praveenkumar, P., Rayappan, J.B.B. and Amirtharajan, R., "DNA chaos blend to secure medical privacy", IEEE Transactions on Nanobioscience, Vol. 16, No. 8, (2017), 850-858. doi: 10.1109/TNB.2017.2780881.
  21. Wang, X. and Zhang, H.-l., "A novel image encryption algorithm based on genetic recombination and hyper-chaotic systems", Nonlinear Dynamics, Vol. 83, No. 1, (2016), 333-346. doi: 10.1007/s11071-015-2330-8.
  22. Pujari, S.K., Bhattacharjee, G. and Bhoi, S., "A hybridized model for image encryption through genetic algorithm and DNA sequence", Procedia Computer Science, Vol. 125, (2018), 165-171. doi: 10.1016/j.procs.2017.12.023.
  23. Sezavar, A., Farsi, H. and Mohamadzadeh, S., "A modified grasshopper optimization algorithm combined with cnn for content based image retrieval", International Journal of Engineering, Transactions A: Basics, Vol. 32, No. 7, (2019), 924-930. doi: 10.5829/ije.2019.32.07a.04.
  24. Coello, C.A.C., "Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: A survey of the state of the art", Computer Methods in Applied Mechanics and Engineering, Vol. 191, No. 11-12, (2002), 1245-1287. doi: 10.1016/S0045-7825(01)00323-1.
  25. Knuth, D.E., Theartofcomputerprogramming: Sortingandsearching. 1973, Addison-Wesley, Reading, Massachusetts.
  26. Hussain, I., Azam, N.A. and Shah, T., "Stego optical encryption based on chaotic s-box transformation", Optics & Laser Technology, Vol. 61, (2014), 50-56. doi: 10.1016/j.optlastec.2014.01.018.
  27. Ahmad, M., Alam, M.Z., Umayya, Z., Khan, S. and Ahmad, F., "An image encryption approach using particle swarm optimization and chaotic map", International Journal of Information Technology, Vol. 10, No. 3, (2018), 247-255. doi: 10.1007/s41870-018-0099-y.
  28. Jolfaei, A. and Mirghadri, A., "A new approach to measure quality of image encryption", International Journal of Computer and Network Security, Vol. 2, No. 8, (2010), 38-44, doi: 10.12928/TELKOMNIKA.v17i6.10488.
  29. Norouzi, B., Mirzakuchaki, S., Seyedzadeh, S.M. and Mosavi, M.R., "A simple, sensitive and secure image encryption algorithm based on hyper-chaotic system with only one round diffusion process", Multimedia Tools and Applications, Vol. 71, No. 3, (2014), 1469-1497. doi: 10.1007/s11042-012-1292-9.
  30. Farwa, S., Muhammad, N., Shah, T. and Ahmad, S., "A novel image encryption based on algebraic s-box and arnold transform", 3D Research, Vol. 8, No. 3, (2017), 1-14, doi: 10.1007/s13319-017-0135-x