Implementation of modified GSO based magic cube keys generation in cryptography

Authors

DOI:

https://doi.org/10.15587/1729-4061.2021.225508

Keywords:

modified galactic swarm optimization (GSO), magic cube, key generation, cryptography

Abstract

Over the last few decades, tremendous and exponential expansion in digital contents together with their applications has emerged. The Internet represents the essential leading factor for this expansion, which provides low-cost communication tools worldwide. However, the main drawback of the Internet is related to security problems. In order to provide secure communication, enormous efforts have been spent in the cryptographic field. Recently, cryptographic algorithms have become essential for increasing information safety. However, these algorithms require random keys and can be regarded as compromised when the random keys are cracked via the attackers. Therefore, it is substantial that the generation of keys should be random and hard to crack. In this paper, this is guaranteed via one of the most efficient nature-inspired algorithms emerged by inspiring the movements of stars, galaxies, and galaxy superclusters in the cosmos that can be utilized with a mathematical model (magic cube) for generating hardly cracking random number keys. In the proposed cryptographic system, the Modified Galactic Swarm Optimization (GSO) algorithm has been utilized in which every row and column of magic cube faces are randomly rotated until reaching the optimal face, and the optimal random elements are selected as optimal key from the optimal face. The generated optimized magic cube keys are used with several versions of RC6 algorithms to encrypt various secret texts. Furthermore, these generated keys are also used for encrypting images using the logical XOR operation. The obtained results of NIST tests proved that the generated keys are random and uncorrelated. Moreover, the security of the proposed cryptographic system was proved

Author Biographies

Alaa Noori Mazher, University of Technology

Assistant Professor

Department of Computer Science

Jumana Waleed, University of Diyala

PhD, Assistant Professor

Department of Computer Science

College of Science

References

  1. Ruzhentsev, V., Onishchenko, Y. (2017). Development of the approach to proving the security of block ciphers to impossible differential attack. Eastern-European Journal of Enterprise Technologies, 4 (4 (88)), 28–33. doi: https://doi.org/10.15587/1729-4061.2017.108413
  2. Mazhar, A. N., Naser, E. F. (2020). Hiding the Type of Skin Texture in Mice based on Fuzzy Clustering Technique. Baghdad Science Journal, 17 (3), 967–972. doi: https://doi.org/10.21123/bsj.2020.17.3(suppl.).0967
  3. Indrasena Reddy, M., Siva Kumar, A. P., Subba Reddy, K. (2020). A secured cryptographic system based on DNA and a hybrid key generation approach. Biosystems, 197, 104207. doi: https://doi.org/10.1016/j.biosystems.2020.104207
  4. Waleed, J., Jun, H. D., Hameed, S. (2015). An Optimized Digital Image Watermarking Technique Based on Cuckoo Search (CS). ICIC Express Letters. Part B, Applications: an international journal of research and surveys, 6 (10), 2629–2634.
  5. Kaya, E., Uymaz, S. A., Kocer, B. (2018). Boosting galactic swarm optimization with ABC. International Journal of Machine Learning and Cybernetics, 10 (9), 2401–2419. doi: https://doi.org/10.1007/s13042-018-0878-6
  6. Jaya Krishna, G., Ravi, V., Nagesh Bhattu, S. (2018). Key generation for plain text in stream cipher via bi-objective evolutionary computing. Applied Soft Computing, 70, 301–317. doi: https://doi.org/10.1016/j.asoc.2018.05.025
  7. Sudeepa, K. B., Aithal, G., Rajinikanth, V., Satapathy, S. C. (2020). Genetic algorithm based key sequence generation for cipher system. Pattern Recognition Letters, 133, 341–348. doi: https://doi.org/10.1016/j.patrec.2020.03.015
  8. Zhu, Z., Wang, C., Chai, H., Yu, H. (2011). A Chaotic Image Encryption Scheme Based on Magic Cube Transformation. 2011 Fourth International Workshop on Chaos-Fractals Theories and Applications. doi: https://doi.org/10.1109/iwcfta.2011.75
  9. Feng, X., Tian, X., Xia, S. (2011). A novel image encryption algorithm based on fractional fourier transform and magic cube rotation. 2011 4th International Congress on Image and Signal Processing. doi: https://doi.org/10.1109/cisp.2011.6100319
  10. Rajavel, D., Shantharajah, S. P. (2012). Cubical key generation and encryption algorithm based on hybrid cube's rotation. International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012). doi: https://doi.org/10.1109/icprime.2012.6208340
  11. Helmy, M., El-Rabaie, E.-S. M., Eldokany, I. M., El-Samie, F. E. A. (2017). 3-D Image Encryption Based on Rubik’s Cube and RC6 Algorithm. 3D Research, 8 (4). doi: https://doi.org/10.1007/s13319-017-0145-8
  12. Wu, Q., Zhu, C., Li, J.-J., Chang, C.-C., Wang, Z.-H. (2016). A magic cube based information hiding scheme of large payload. Journal of Information Security and Applications, 26, 1–7. doi: https://doi.org/10.1016/j.jisa.2015.08.003
  13. Redha, D. A., Mohsen, M. M. A. (2017). Multi-level Security Based on Dynamic Magic Cube and Chaotic Maps. Iraqi Journal of Information Technology, 7 (4), 106–127. doi: https://doi.org/10.34279/0923-007-004-009
  14. Lee, C.-F., Shen, J.-J., Agrawal, S., Wang, Y.-X., Lee, Y.-H. (2020). Data Hiding Method Based on 3D Magic Cube. IEEE Access, 8, 39445–39453. doi: https://doi.org/10.1109/access.2020.2975385
  15. Nguyen, B. M., Tran, T., Nguyen, T., Nguyen, G. (2020). Hybridization of Galactic Swarm and Evolution Whale Optimization for Global Search Problem. IEEE Access, 8, 74991–75010. doi: https://doi.org/10.1109/access.2020.2988717

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Published

2021-02-27

How to Cite

Mazher, A. N., & Waleed, J. (2021). Implementation of modified GSO based magic cube keys generation in cryptography . Eastern-European Journal of Enterprise Technologies, 1(9 (109), 43–49. https://doi.org/10.15587/1729-4061.2021.225508

Issue

Section

Information and controlling system