Skip to main content
SpringerLink
Log in

Entropy Influenced RNA Diffused Quantum Chaos to Conserve Medical Data Privacy

  • Published:
International Journal of Theoretical Physics Aims and scope Submit manuscript

Abstract

Recently, the protection and transferring of medical images among peers in the established communication link has become a significant security threat. In this paper, to curtail the threats posed on the open communal channel, RNA diffused Quantum Chaos (RQC) encryption algorithm for colour Digital Imaging and Communications in Medicines (DICOM) image is proposed for the first time. It employs entropy estimation and updates it in the key stream generation and thereby avoids the limitation in traditional encryption schemes of scrambling the position of the pixels before diffusion. The proposed encryption scheme uses Novel Enhanced Quantum Representation (NEQR) and qubit arrangement to store the grayscale value of every pixel in the DICOM image. Using the key generated from the chaotic map, the image is diffusedusing the quantum Controlled-NOT(CNOT)gate. Further, to enrich the diffusion process, Deoxyribonucleic Acid (DNA) transcript Ribo Nucleic Acid (RNA) is used to diffuse the quantum bits in the image matrix with its self-complementary sequence generation. The diffused image is permuted by incorporating the circular shift operation. The efficiency of the proposed algorithm has been validated by using encryption quality metrics.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  1. Diaconu, A.-V.: Circular inter–intra pixels bit-level permutation and chaos-based image encryption. Inf. Sci. (NY). 355–356, 314–327 (2016). https://doi.org/10.1016/J.INS.2015.10.027

    Article  Google Scholar 

  2. Hua, Z., Yi, S., Zhou, Y.: Medical image encryption using high-speed scrambling and pixel adaptive diffusion. Signal Process. 144, 134–144 (2018). https://doi.org/10.1016/j.sigpro.2017.10.004

    Article  Google Scholar 

  3. Praveenkumar, P., Kerthana Devi, N., Ravichandran, D., Avila, J., Thenmozhi, K., Rayappan, J.B.B., Amirtharajan, R.: Transreceiving of encrypted medical image – a cognitive approach. Multimed. Tools Appl. 77, 1–26 (2017). https://doi.org/10.1007/s11042-017-4741-7

    Google Scholar 

  4. Feynman, R.P.: Simulating physics with computers by R P Feynman.Pdf. Int. J. Theor. Phys. 21, 467–488 (1982)

    Article  Google Scholar 

  5. Sun B, Le PQ, Iliyasu AM, Yan F, Garcia JA, Dong F, Hirota K (2011) A Multi-Channel Representation for Images on Quantum Computers Using the RGB D Color Space. 1

  6. Venegas-Andraca, S.E., Ball, J.L.: Processing images in entangled quantum systems. Quantum Inf. Process. 9, 1–11 (2010). https://doi.org/10.1007/s11128-009-0123-z

    Article  MathSciNet  Google Scholar 

  7. Latorre JI (2005) Image compression and entanglement. 4

  8. Zhang, Y., Lu, K., Gao, Y., Wang, M.: NEQR: a novel enhanced quantum representation of digital images. Quantum Inf. Process. 12, 2833–2860 (2013). https://doi.org/10.1007/s11128-013-0567-z

    Article  ADS  MathSciNet  MATH  Google Scholar 

  9. Zhou R-G, Wu Q, Zhang M-Q, Shen C-Y (2012) A quantum image encryption algorithm based on quantum image geometric transformations. Pattern Recognit. Chinese Conf. CCPR 2012, 321, 480–487. https://doi.org/10.1007/978-3-642-33506-8

  10. Song, X.H., Wang, S., Liu, S., Abd El-Latif, A.A., Niu, X.M.: A dynamic watermarking scheme for quantum images using quantum wavelet transform. Quantum Inf. Process. 12, 3689–3706 (2013). https://doi.org/10.1007/s11128-013-0629-2

    Article  ADS  MathSciNet  MATH  Google Scholar 

  11. Yang, Y.-G., Jia, X., Sun, S.-J., Pan, Q.-X.: Quantum cryptographic algorithm for color images using quantum Fourier transform and double random-phase encoding. Inf. Sci. (NY). 277, 445–457 (2014). https://doi.org/10.1016/j.ins.2014.02.124

    Article  Google Scholar 

  12. Beheri MH, Amin M, Song X, El-Latif AAA (2016) Quantum Image Encryption Based on Scrambling- Diffusion ( SD ) Approach. Front. Signal Process 43–47

  13. Le, P.Q., Dong, F., Hirota, K.: A flexible representation of quantum images for polynomial preparation, image compression, and processing operations. Quantum Inf. Process. 10, 63–84 (2011). https://doi.org/10.1007/s11128-010-0177-y

    Article  MathSciNet  MATH  Google Scholar 

  14. Zhou, R.G., Sun, Y.J., Fan, P.: Quantum image gray-code and bit-plane scrambling. Quantum Inf. Process. 14, 1717–1734 (2015). https://doi.org/10.1007/s11128-015-0964-6

    Article  ADS  MathSciNet  MATH  Google Scholar 

  15. Yan, F., Chen, K., Venegas-Andraca, S.E., Zhao, J.: Quantum image rotation by an arbitrary angle. Quantum Inf. Process. 16, 1–20 (2017). https://doi.org/10.1007/s11128-017-1733-5

    Article  MathSciNet  MATH  Google Scholar 

  16. Wu Y, Member S, Noonan JP, Member L (2011) NPCR and UACI randomness tests for image encryption. Cyber Journals Multidiscip. Journals Sci. Technol. J. Sel. Areas Telecommun. 31–38

  17. Abd El-Latif, A.A., Abd-El-Atty, B., Talha, M.: Robust encryption of quantum medical images. IEEE Access. 6, 1073–1081 (2018). https://doi.org/10.1109/ACCESS.2017.2777869

    Article  Google Scholar 

  18. Li, H.-S., Li, C., Chen, X., Xia, H.: Quantum image encryption algorithm based on NASS. Int. J. Theor. Phys. 57, 3745–3760 (2018). https://doi.org/10.1007/s10773-018-3887-z

    Article  MathSciNet  Google Scholar 

  19. Zhou, N., Yan, X., Liang, H., Tao, X., Li, G.: Multi-image encryption scheme based on quantum 3D Arnold transform and scaled Zhongtang chaotic system. Quantum Inf. Process. 17(338), (2018). https://doi.org/10.1007/s11128-018-2104-6

  20. Wang J, Geng Y-C, Han L, Liu J-Q (2018) Quantum image encryption algorithm based on quantum key image. Int. J. Theor. Phys. 1–15. https://doi.org/10.1007/s10773-018-3932-y

  21. Zhou, N., Hu, Y., Gong, L., Li, G.: Quantum image encryption scheme with iterative generalized Arnold transforms and quantum image cycle shift operations. Quantum Inf. Process. 16, 1–23 (2017). https://doi.org/10.1007/s11128-017-1612-0

    Article  ADS  MathSciNet  MATH  Google Scholar 

  22. Zhou, N.R., Hua, T.X., Gong, L.H., Pei, D.J., Liao, Q.H.: Quantum image encryption based on generalized Arnold transform and double random-phase encoding. Quantum Inf. Process. 14, 1193–1213 (2015). https://doi.org/10.1007/s11128-015-0926-z

    Article  ADS  MathSciNet  MATH  Google Scholar 

  23. Li, X.-Z., Chen, W.-W., Wang, Y.-Q.: Quantum image compression-encryption scheme based on quantum discrete cosine transform. Int. J. Theor. Phys. 57, 2904–2919 (2018). https://doi.org/10.1007/s10773-018-3810-7

    Article  Google Scholar 

  24. Wang, X., Liu, C.: A novel and effective image encryption algorithm based on chaos and DNA encoding. Multimed. Tools Appl. 76, 6229–6245 (2017). https://doi.org/10.1007/s11042-016-3311-8

    Article  Google Scholar 

  25. Ye, G., Pan, C., Huang, X., Zhao, Z., He, J.: A chaotic image encryption algorithm based on information entropy. Int. J. Bifurc. Chaos. 28, 1850010 (2018). https://doi.org/10.1142/S0218127418500104

    Article  MathSciNet  MATH  Google Scholar 

  26. Higgs, P.G.: RNA secondary structure: physical and computational aspects. Q. Rev. Biophys. 33, 199–253 (2000)

    Article  Google Scholar 

  27. Shabash, B., Wiese, K.C.: RNA visualization: relevance and the current state-of-the-art focusing on pseudoknots. IEEE/ACM Trans. Comput. Biol. Bioinform. 14, 696–712 (2017). https://doi.org/10.1109/TCBB.2016.2522421

    Article  Google Scholar 

Download references

Acknowledgements

The authors wish to acknowledge SASTRA Deemed to be University, Thanjavur, India for extending infrastructural support to carry out this work.

Author information

Authors and Affiliations

  1. Department of Electronics & Communication Engineering, School of Electrical & Electronics Engineering, SASTRA Deemed University, Thanjavur, 613 401, India

    R. Santhiya Devi, K. Thenmozhi, John Bosco Balaguru Rayappan, Rengarajan Amirtharajan & Padmapriya Praveenkumar

Authors
  1. R. Santhiya Devi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. Thenmozhi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. John Bosco Balaguru Rayappan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rengarajan Amirtharajan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Padmapriya Praveenkumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Padmapriya Praveenkumar.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Devi, R.S., Thenmozhi, K., Rayappan, J.B.B. et al. Entropy Influenced RNA Diffused Quantum Chaos to Conserve Medical Data Privacy. Int J Theor Phys 58, 1937–1956 (2019). https://doi.org/10.1007/s10773-019-04088-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10773-019-04088-6

Keywords

Search

Navigation