Skip to main content
SpringerLink
Log in

Analysis of zig-zag scan based modified feedback convolution algorithm against differential attacks and its application to image encryption

  • Published:
Applied Intelligence Aims and scope Submit manuscript

Abstract

In this paper, a novel zig-zag scan-based feedback convolution algorithm for image encryption against differential attacks is proposed. The two measures Number of Pixel Change Rate (NPCR) and Unified Average Changed Intensity (UACI) are commonly utilized for analyzing the differential attacks. From the study of the existing papers, even though high Number of Pixel Change Rate and Unified Average Changed Intensity values are obtained, a few values lie in the critical range of α-level significance which in turn increase the possibility of differential attacks. To overcome differential attacks, two aspects of scanning with different test cases are analyzed and from these analyses, it is concluded that zig-zag scan based feedback convolution in forward and reverse direction achieves good Number of Pixel Change Rate and Unified Average Changed Intensity without critical values. Zig-zag scan based feedback convolution in forward and reverse direction is enforced for key sequence generation and applied in diffusion process to achieve high level of security. Moreover, plain image related initial seed is also generated to overcome the chosen/known plain text attacks. Both numerical and theoretical analyses are performed to prove that the proposed encryption method is resistant to differential attacks. General security measures are carried out for the proposed method to validate its security level. From the simulations, it is shown that the proposed methodology has good keyspace, high key sensitivity, good randomness, and uniform distribution of cipher image pixels.

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.

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

Similar content being viewed by others

References

  1. Ahmad M, Sundararajan D (1987) A fast implementation of two-dimensional convolution algorithm for image-processing applications. IEEE Trans Circ Syst 34(5):577–579

    Article  Google Scholar 

  2. Brindha M, Gounden NA (2016) A chaos based image encryption and lossless compression algorithm using hash table and chinese remainder theorem. Appl Soft Comput 40:379–390

    Article  Google Scholar 

  3. Cao C, Sun K, Liu W (2018) A novel bit-level image encryption algorithm based on 2d-licm hyperchaotic map. Signal Process 143:122–133

    Article  Google Scholar 

  4. Chai X, Gan Z, Yuan K, Chen Y, Liu X (2019) A novel image encryption scheme based on dna sequence operations and chaotic systems. Neural Comput Applic 31(1):219–237

    Article  Google Scholar 

  5. Chen Jx, Zhu Zl, Fu C, Yu H, Zhang Lb (2015) A fast chaos-based image encryption scheme with a dynamic state variables selection mechanism. Commun Nonlinear Sci Numer Simul 20(3):846–860

    Article  Google Scholar 

  6. Chen Y, Liao X, Wong KW (2006) Chosen plaintext attack on a cryptosystem with discretized skew tent map. IEEE Trans Circ Syst II: Express Briefs 53(7):527–529

    Article  Google Scholar 

  7. Dong C (2014) Color image encryption using one-time keys and coupled chaotic systems. Signal Process Image Commun 29(5):628–640

    Article  Google Scholar 

  8. Enayatifar R, Abdullah AH, Isnin IF, Altameem A, Lee M (2017) Image encryption using a synchronous permutation-diffusion technique. Opt Lasers Eng 90:146–154

    Article  Google Scholar 

  9. Fu C, Lin Bb, Miao Ys, Liu X, Chen Jj (2011) A novel chaos-based bit-level permutation scheme for digital image encryption. Opt Commun 284(23):5415–5423

    Article  Google Scholar 

  10. Gao H, Gao T (2019) Double verifiable image encryption based on chaos and reversible watermarking algorithm. Multimed Tools Appl 78(6):7267–7288

    Article  Google Scholar 

  11. Hsiao HI, Lee J (2015) Color image encryption using chaotic nonlinear adaptive filter. Signal Process 117:281–309

    Article  Google Scholar 

  12. Hua Z, Zhou Y, Huang H (2019) Cosine-transform-based chaotic system for image encryption. Inform Sci 480:403–419

    Article  Google Scholar 

  13. Huo D, Zhou Df, Yuan S, Yi S, Zhang L, Zhou X (2019) Image encryption using exclusive-or with dna complementary rules and double random phase encoding. Phys Lett A 383(9):915–922

    Article  Google Scholar 

  14. Jakimoski G, Kocarev L (2001) Chaos and cryptography: block encryption ciphers based on chaotic maps. IEEE Trans Circ Syst I: Fund Theory Appl 48(2):163–169

    Article  MathSciNet  Google Scholar 

  15. Kandar S, Chaudhuri D, Bhattacharjee A, Dhara BC (2019) Image encryption using sequence generated by cyclic group. J Inform Secur Appl 44:117–129

    Google Scholar 

  16. Kocarev L (2001) Chaos-based cryptography: a brief overview. IEEE Circ Syst Mag 1(3):6–21

    Article  Google Scholar 

  17. Lan R, He J, Wang S, Gu T, Luo X (2018) Integrated chaotic systems for image encryption. Signal Process 147:133–145

    Article  Google Scholar 

  18. Li C, Liu Y, Zhang LY, Wong KW (2014) Cryptanalyzing a class of image encryption schemes based on chinese remainder theorem. Signal Process Image Commun 29(8):914–920

    Article  Google Scholar 

  19. Li S, Zheng X (2002) Cryptanalysis of a chaotic image encryption method. In: IEEE International symposium on circuits and systems, 2002. ISCAS 2002, vol 2. IEEE, pp II–II

  20. Li Y, Wang C, Chen H (2017) A hyper-chaos-based image encryption algorithm using pixel-level permutation and bit-level permutation. Opt Lasers Eng 90:238–246

    Article  Google Scholar 

  21. Li Z, Li K, Wen C, Soh YC (2003) A new chaotic secure communication system. IEEE Trans Commun 51(8):1306–1312

    Article  Google Scholar 

  22. Liu H, Kadir A, Sun X (2017) Chaos-based fast colour image encryption scheme with true random number keys from environmental noise. IET Image Process 11(5):324–332

    Article  Google Scholar 

  23. Liu H, Wan H, Chi KT, Lü J (2016) An encryption scheme based on synchronization of two-layered complex dynamical networks. IEEE Trans Circ Syst I: Regular Papers 63(11):2010–2021

    Google Scholar 

  24. Liu Y, Tong X, Ma J (2016) Image encryption algorithm based on hyper-chaotic system and dynamic s-box. Multimed Tools Appl 75(13):7739–7759

    Article  Google Scholar 

  25. Ludwig J (2013) Image convolution. Portland State University

  26. Luo Y, Yu J, Lai W, Liu L (2019) A novel chaotic image encryption algorithm based on improved baker map and logistic map. Multimed Tools Appl, 1–21

  27. Masuda N, Aihara K (2002) Cryptosystems with discretized chaotic maps. IEEE Trans Circ Syst I: Fund Theory Appl 49(1):28–40

    Article  MathSciNet  Google Scholar 

  28. Murugan B, Gounder AGN (2016) Image encryption scheme based on block-based confusion and multiple levels of diffusion. IET Comput Vis 10(6):593–602

    Article  Google Scholar 

  29. Rahman SMM, Hossain MA, Mouftah H, El Saddik A, Okamoto E (2012) Chaos-cryptography based privacy preservation technique for video surveillance. Multimed Syst 18(2):145–155

    Article  Google Scholar 

  30. Rajagopalan S, Sharma S, Arumugham S, Upadhyay HN, Rayappan JBB, Amirtharajan R (2019) Yrbs coding with logistic map–a novel sanskrit aphorism and chaos for image encryption. Multimed Tools Appl 78 (8):10513–10541

    Article  Google Scholar 

  31. Rhouma R, Solak E, Belghith S (2010) Cryptanalysis of a new substitution–diffusion based image cipher. Commun Nonlinear Sci Numer Simul 15(7):1887–1892

    Article  MathSciNet  Google Scholar 

  32. Seyedzadeh SM, Mirzakuchaki S (2012) A fast color image encryption algorithm based on coupled two-dimensional piecewise chaotic map. Signal Process 92(5):1202–1215

    Article  Google Scholar 

  33. Shannon CE (1949) Communication theory of secrecy systems. Bell Labs Techn J 28(4):656–715

    Article  MathSciNet  Google Scholar 

  34. Teng L, Wang X (2012) A bit-level image encryption algorithm based on spatiotemporal chaotic system and self-adaptive. Opt Commun 285(20):4048–4054

    Article  Google Scholar 

  35. Wang B, Zheng X, Zhou S, Zhou C, Wei X, Zhang Q, Che C (2014) Encrypting the compressed image by chaotic map and arithmetic coding. Optik-Int J Light Electron Opt 125(20):6117–6122

    Article  Google Scholar 

  36. Wu Y, Noonan JP, Agaian S (2011) Npcr and uaci randomness tests for image encryption. Cyber journals: multidisciplinary journals in science and technology. J Selected Areas Telecommun (JSAT) 1(2):31–38

    Google Scholar 

  37. Yavuz E (2019) A novel chaotic image encryption algorithm based on content-sensitive dynamic function switching scheme. Opt Laser Technol 114:224–239

    Article  Google Scholar 

  38. Ye G, Huang X (2016) An image encryption algorithm based on autoblocking and electrocardiography. IEEE MultiMedia 23(2):64–71

    Article  Google Scholar 

  39. Ye R (2011) A novel chaos-based image encryption scheme with an efficient permutation-diffusion mechanism. Opt Commun 284(22):5290–5298

    Article  Google Scholar 

  40. Zhou Y, Bao L, Chen CP (2013) Image encryption using a new parametric switching chaotic system. Signal Process 93(11):3039–3052

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology, Tiruchirappalli, Tamilnadu, India

    R. Vidhya & M. Brindha

  2. Department of Electrical and Electronics and Engineering, National Institute of Technology, Tiruchirappalli, Tamilnadu, India

    N. Ammasai Gounden

Authors
  1. R. Vidhya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. Brindha
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. N. Ammasai Gounden
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. Brindha.

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

Vidhya, R., Brindha, M. & Gounden, N.A. Analysis of zig-zag scan based modified feedback convolution algorithm against differential attacks and its application to image encryption. Appl Intell 50, 3101–3124 (2020). https://doi.org/10.1007/s10489-020-01697-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10489-020-01697-1

Keywords

Search

Navigation