DOI: https://doi.org/10.14710/jtsiskom.2021.14038

Enhanced image security using residue number system and new Arnold transform

1Department of Computer Science, Faculty of Communication and Information Technology, Kwara State University, Malete, Kwara State, Nigeria

2Department of Computer Science, College of Natural and Applied Sciences, Summit University, Offa, Kwara State, Nigeria

3Department of Telecommunication Science, Faculty of Communication and Information Sciences, University of Ilorin, Kwara State, Nigeria

Received: 5 Jan 2021; Revised: 8 Jul 2021; Accepted: 18 Jul 2021; Published: 31 Oct 2021.
Open Access Copyright (c) 2021 The Authors. Published by Department of Computer Engineering, Universitas Diponegoro under https://creativecommons.org/licenses/by-sa/4.0s.

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Abstract
This paper aims to improve the image scrambling and encryption effect in traditional two-dimensional discrete Arnold transform by introducing a new Residue number system (RNS) with three moduli and the New Arnold Transform. The study focuses on improving the classical discrete Arnold transform with quasi-affine properties, applying image scrambling and encryption research. The design of the method is explicit to three moduli set {2n, 2n+1+1, 2n+1-1}. These moduli set includes equalized and shapely moduli leading to the effective execution of the residue to binary converter. The study employs an arithmetic residue to the binary converter and an improved Arnold transformation algorithm. The encryption process uses MATLAB to accept a digital image input and subsequently convert the image into an RNS representation. The images are connected as a group. The resulting encrypted image uses the Arnold transformation algorithm. The encrypted image is used as input at decryption using the anti-Arnold (Reverse Arnold) transformation algorithm to convert the picture to the original RNS (original pixel value). Then the RNS was used to retransform the original RNS to its binary form. Security analysis tests, like histogram analysis, keyspace, key sensitivity, and correlation coefficient analysis, were administered on the encrypted image. Results show that the hybrid system can use the improved Arnold transform algorithm with better security and no constraint on image width and size.
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Keywords: cryptosystem; forward conversion; residue number system; reverse conversion
Funding: College of Natural and Applied Science, Summit University

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Section: Original Research Articles
Language : EN
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  1. D. P. Oyinloye and K. A. Gbolagade, “An improved image scrambling algorithm using {2n -1, 2n, 2n+1},” Computing and Information Systems Journal, vol. 22, no. 3, pp. 1-7, 2018
  2. D. Peter, “Image encryption system based on length three moduli set,” International Journal of Computer Applications, vol. 179, no. 42, pp. 12–14, 2018. doi: 10.5120/ijca2018916989
  3. A. N. Babatunde, R. G. Jimoh, and K. A. Gbolagade, “An algorithm for a residue number system based video encryption system,” Annals Computer Science Series Journal, vol. XIV, pp. 137–145, 2016
  4. S. Alhassan and K. A. Gbolagade, “Enhancement of the security of a digital image using the moduli set,” International Journal of Advanced Research in Computer Engineering & Technology, vol. 2, no. 7, pp. 2223–2229, 2013
  5. A. N. Babatunde, "Methodology for image cryptosystem based on a gray code number system," Computing and Information Systems Journal, vol. 23, no. 2, pp. 1-5, 2019
  6. I. Z. Alhassan and E. D. Ansong, “Enhancing image security during transmission using residue number system and k-shuffle ”, Earthline Journal of Mathematical Sciences, vol. 4, no. 2, pp. 399–424, 2020. doi: 10.34198/ejms.4220.399424
  7. E. Y. Baagyere, P. A. N. Agbedemnab, Z. Qin, M. I. Daabo, and Z. Qin, “A multi-layered data encryption and decryption scheme based on genetic algorithm and residual numbers,” IEEE Access, vol. 8, pp. 100438–100447, 2020. doi: 10.1109/ACCESS.2020.2997838
  8. M. Boussif, N. Aloui, and A. Cherif, “Securing DICOM images by a new encryption algorithm using Arnold transform and Vigenère cipher,” IET Image Processing, vol. 14, no. 6, pp. 1209-1216, 2020. doi: 10.1049/iet-ipr.2019.0042
  9. J. Wu, Z. Liu, J. Wang, L. Hu, and S. Liu, “A compact image encryption system based on Arnold transformation,” Multimedia Tools and Applications, vol. 80, pp. 2647–2661, 2021. doi: 10.1007/s11042-020-09828-z
  10. A. Alhassan, I. Saeed, and P. A. Agbedemnab, “The Huffman’s method of secured data encoding and error correction using residue number system (RNS),” Communications on Applied Electronics, vol. 2, no. 9, pp. 14–18, 2015. doi: 10.5120/cae2015651844
  11. D. A. Huffman, “A method for the construction of minimum-redundancy codes,” Resonance, vol. 11, no. 2, pp. 91–99, 1952. doi: 10.1007/bf02837279
  12. C. M. Wu, “An improved discrete Arnold transform and its application in image scrambling and encryption,” Acta Physica Sinica, vol. 63, no. 9, pp. 1–20, 2014. doi: 10.7498/aps.63.090504
  13. J. C. Bajard, J. Eynard, N. Merkiche, and T. Plantard, “RNS arithmetic approach in lattice-based cryptography: accelerating the ‘rounding-off’ core procedure,” in the 22nd Symposium on Computer Arithmetic, Lyon, France, Jun. 2015, pp. 113–120. doi: 10.1109/ARITH.2015.30
  14. B. Yosefnezhad Irani, P. Ayubi, F. Amani Jabalkandi, M. Yousefi Valandar, and M. Jafari Barani, “Digital image scrambling based on a new one-dimensional coupled Sine map,” Nonlinear Dynamics, vol. 97, no. 4, pp. 2693–2721, 2019. doi: 10.1007/s11071-019-05157-5
  15. P. V. N. Reddy and R. Karumuri, “Image encryption and decryption in RNS domain based on {2n , 22n+1-1, 2n+1, 2n-1} moduli set,” in International Conference on Communication and Electronics Systems, Coimbatore, India, Oct. 2016, pp. 1–5. doi: 10.1109/cesys.2016.7889984
  16. P. K. Singh, B. Jana, and K. Datta, “Superpixel based robust reversible data hiding scheme exploiting Arnold transform with DCT and CA,” Journal of King Saud University - Computer and Information Sciences, InPress, 2020. doi: 10.1016/j.jksuci.2020.09.014
  17. A. Belazi, A. A. Abd El-Latif, A. V. Diaconu, R. Rhouma, and S. Belghith, “Chaos-based partial image encryption scheme based on linear fractional and lifting wavelet transforms,” Optics and Laser Engineering, vol. 88, pp. 37–50, 2017. doi: 10.1016/j.optlaseng.2016.07.010
  18. S. Noshadian, A. Ebrahimzade, and S. J. Kazemitabar, “Optimizing chaos based image encryption,” Multimedia Tools and Application, vol. 77, no. 19, pp. 25569–25590, 2018. doi: 10.1007/s11042-018-5807-x
  19. R. Kumar, S. Kini, L. Akshatha, and B. G. Deeksha, “Cheat immune visual cryptographic for secure transmission of images,” International Journal of Engineering and Advanced Technology, vol. 8, no. 4, pp. 1175–1181, 2019
  20. Q. Sun, P. Guan, Y. Qiu, and Y. Xue, “A novel digital image encryption method based on one-dimensional random scrambling,” in International Conference on Fuzzy Systems and Knowledge Discovery, Chongqing, China, May 2012, pp. 1669–1672. doi: 10.1109/FSKD.2012.6233963
  21. M. Ding and F. Jing, "Digital image encryption algorithm based on improved Arnold transform," in International Forum on Information Technology and Applications, Kunming, China, Jul. 2010, pp. 174-176. doi: 10.1109/IFITA.2010.17
  22. Z. Bashir, T. Rashid, and S. Zafar, “Hyperchaotic dynamical system based image encryption scheme with time-varying delays,” Pacific Science Review A: Natural Science and Engineering, vol. 18, no. 3, pp. 254-260, 2016. doi: 10.1016/j.psra.2016.11.003
  23. A. N. Babatunde, E. R. Jimoh, O. Oshodi, and O. A. Alabi, “Performance analysis of gray code number system in image security,” Jurnal Teknologi dan Sistem Komputer, vol. 7, no. 4, pp. 141–146, 2019. doi: 10.14710/jtsiskom.7.4.2019.141-146

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