Evolutionary Intelligence

, Volume 11, Issue 1–2, pp 53–71 | Cite as

Medical image security enhancement using two dimensional chaotic mapping optimized by self-adaptive grey wolf algorithm

  • Srinivas KoppuEmail author
  • V. Madhu Viswanatham
Special Issue


The development of encryption and decryption plays a vital role in the field of security. Recently, Chaos-based security has suggested the reliable and efficient way of securing the images. In this paper, Self-Adaptive Grey Wolf Optimization (GWO) is proposed for optimizing 2-dimensional Logistic Chaotic Mapping (2DCM). Further, the security analysis of the proposed method is performed using different comparison such as key sensitivity, histogram analysis, adjacent pixel autocorrelation, information entropy, attacks, quality of encryption, Chi square test etc. Moreover, analytical outcomes are compared with the conventional algorithms like standard encryption and decryption, Genetic Algorithm (GA) and GWO. The experimental result stated that the proposed method is key sensitive and opposed to the general attacks during the encryption and decryption of images.


Encryption Decryption 2DCM GWO Modified GWO 



  1. 1.
    Zhou N, Pan S, Cheng S, Zhou Z (2016) Image compression—encryption scheme based on hyper-chaotic system and 2D compressive sensing. Opt Laser Technol 82:121–133CrossRefGoogle Scholar
  2. 2.
    Liu W, Sun K, Zhu C (2016) A fast image encryption algorithm based on chaotic map. Opt Lasers Eng 84:26–36CrossRefGoogle Scholar
  3. 3.
    Murugan B, Nanjappa Gounder AG (2016) Image encryption scheme based on block-based confusion and multiple levels of diffusion. IET Comput Vision 10(6):593–602CrossRefGoogle Scholar
  4. 4.
    Giovannozzi M (1993) Analysis of the stability domain for the Henon map. Phys Lett A 182(2–3):255–260MathSciNetCrossRefGoogle Scholar
  5. 5.
    Wadi SM, Zainal N (2015) Decomposition by binary codes-based speedy image encryption algorithm for multiple applications. IET Image Proc 9(5):413–423CrossRefGoogle Scholar
  6. 6.
    Sun Y, Xu R, Chen L, Hu X (2015) Image compression and encryption scheme using fractal dictionary and Julia set. IET Image Proc 9(3):173–183CrossRefGoogle Scholar
  7. 7.
    Belazi A, Abd El-Latif AA, Belghith S (2016) A novel image encryption scheme based on substitution-permutation network and chaos. Sig Process 128:155–170CrossRefGoogle Scholar
  8. 8.
    Li J, Liu H (2013) Colour image encryption based on advanced encryption standard algorithm with two-dimensional chaotic map. IET Inf Secur 7(4):265–270MathSciNetCrossRefGoogle Scholar
  9. 9.
    Hua Z, Zhou Y, Pun CM, Philip Chen CL (2015) 2D Sine Logistic modulation map for image encryption. Inf Sci 297:80–94CrossRefGoogle Scholar
  10. 10.
    Cheddad A, Condell J, Curran K, McKevitt P (2010) Digital image steganography: survey and analysis of current methods. Sig Process 90(3):727–752CrossRefGoogle Scholar
  11. 11.
    Tseng YC, Chen YY, Pan HK (2002) A secure data hiding scheme for binary images. IEEE Trans Commun 50(8):1227–1231CrossRefGoogle Scholar
  12. 12.
    Zope-Chaudhari S, Venkatachalam P, Buddhiraju KM (2015) Secure dissemination and protection of multispectral images using crypto-watermarking. IEEE J Select Topics Appl Earth Observations Remote Sens 8(11):5388–5394CrossRefGoogle Scholar
  13. 13.
    Philip A (2013) A generalized pseudo-knight? s tour algorithm for encryption of an image. IEEE Potentials 32(6):10–16CrossRefGoogle Scholar
  14. 14.
    Yang M, Bourbakis N, Li S (2004) Data-image-video encryption. IEEE Potentials 23(3):28–34CrossRefGoogle Scholar
  15. 15.
    Wu X, Wang D, Kurths J, Kan H (2016) A novel lossless color image encryption scheme using 2D DWT and 6D hyperchaotic system. Inf Sci 349–350:137–153CrossRefGoogle Scholar
  16. 16.
    Sudharsanan S (2005) Shared key encryption of JPEG color images. IEEE Trans Consum Electron 51(4):1204–1211CrossRefGoogle Scholar
  17. 17.
    Zhang X, Li W, Hu H, Dutta NK (2015) High-speed all-optical encryption and decryption based on two-photon absorption in semiconductor optical amplifiers. IEEE/OSA J Opt Commun Netw 7(4):276–285CrossRefGoogle Scholar
  18. 18.
    Wagh AM, Todmal SR (2015) Eyelids, eyelashes detection algorithm and Hough transform method for noise removal in iris recognition. Int J Comput Appl 112(3)Google Scholar
  19. 19.
    Sunil Kumar BS, Manjunath AS, Christopher S (2018) Improved entropy encoding for high efficient video coding standard. Alex Eng J 57(1):1–9CrossRefGoogle Scholar
  20. 20.
    Kota PN, Gaikwad AN (2017) Optimized scrambling sequence to reduce papr in space frequency block codes based MIMO-OFDM system. J Adv Res Dyn Control Syst 502–525Google Scholar
  21. 21.
    Bhatnagar K, Gupta S (2017) Extending the neural model to study the impact of effective area of optical fiber on laser intensity. Int J Intell Eng Syst 10(4):274–283CrossRefGoogle Scholar
  22. 22.
    Balaji GN, Subashini TS, Chidambaram N (2015) Detection of heart muscle damage from automated analysis of echocardiogram video. IETE J Res 61(3):236–243CrossRefGoogle Scholar
  23. 23.
    Bramhe SS, Dalal A, Tajne D, Marotkar D (2015) Glass shaped antenna with defected ground structure for cognitive radio application. In: International Conference on Computing Communication Control and Automation, Pune, pp 330–333Google Scholar
  24. 24.
    Yarrapragada KSSR, Krishna BB (2017) Impact of tamanu oil-diesel blend on combustion, performance and emissions of diesel engine and its prediction methodology. J Braz Soc Mech Sci Eng 1–15Google Scholar
  25. 25.
    Sreedharan NPN, Ganesan B, Raveendran R, Sarala P, Dennis B, Boothalingam R (2018) Grey Wolf optimisation-based feature selection and classification for facial emotion recognition. IET BiometricsGoogle Scholar
  26. 26.
    Sarkar A, Murugan TS (2017) Cluster head selection for energy efficient and delay-less routing in wireless sensor network. Wireless Netw 1–18Google Scholar
  27. 27.
    Kumar M, Vaish A (2017) Encryption of color images using MSVD in DCST domain. Opt Lasers Eng 88:51–59CrossRefGoogle Scholar
  28. 28.
    Hofbauer H, Uhl A (2016) Identifying deficits of visual security metrics for images. Sig Process Image Commun 46:60–75CrossRefGoogle Scholar
  29. 29.
    Dang PP, Chau PM (2000) Image encryption for secure Internet multimedia applications. IEEE Trans Consum Electron 46(3):395–403CrossRefGoogle Scholar
  30. 30.
    Satish K, Jayakar T, Tobin C, Madhavi K, Murali K (2004) Chaos based spread spectrum image steganography. IEEE Trans Consum Electron 50(2):587–590CrossRefGoogle Scholar
  31. 31.
    Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46–61CrossRefGoogle Scholar
  32. 32.
    Iyapparaja M, Tiwari M (2017) Security policy speculation of user uploaded images on content sharing sites. IOP Conf Ser Mater Sci Eng 263(4):042019CrossRefGoogle Scholar
  33. 33.
    Jain M, Lenka SK, Vasistha SK (2016) Adaptive circular queue image steganography with RSA cryptosystem. Perspect Sci 8:417–420CrossRefGoogle Scholar
  34. 34.
    Sun S (2016) A novel edge based image steganography with 2 k correction and Huffman encoding. Inf Process Lett 116(2):93–99MathSciNetCrossRefGoogle Scholar
  35. 35.
    Zhang D, Zhang F (2014) Chaotic encryption and decryption of JPEG image. Optik Int Light Electron Opt 125(2):717–720CrossRefGoogle Scholar
  36. 36.
    Ye G, Huang X (2016) An image encryption algorithm based on autoblocking and electrocardiography. IEEE MultiMedia 23(2):64–71CrossRefGoogle Scholar
  37. 37.
    Candido R, Soriano DC, Silva MTM, Eisencraft M (2015) Do chaos-based communication systems really transmit chaotic signals? Sig Process 108:412–420CrossRefGoogle Scholar
  38. 38.
    Yang YG, Tian J, Lei H, Zhou YH, Shi WM (2016) Novel quantum image encryption using one-dimensional quantum cellular automata. Inf Sci 345:257–270CrossRefGoogle Scholar
  39. 39.
    Liu Y et al (2016) Light encryption scheme using light-emitting diode and camera image sensor. IEEE Photon J 8(1):1–7Google Scholar
  40. 40.
    Wu HC, Wu NI, Tsai CS, Hwang MS (2005) Image steganographic scheme based on pixel-value differencing and LSB replacement methods. IEEE Proc Vis Image Signal Process 152(5):611–615CrossRefGoogle Scholar
  41. 41.
    Dzwonkowski M, Papaj M, Rykaczewski R (2015) A new quaternion-based encryption method for DICOM images. IEEE Trans Image Process 24(11):4614–4622MathSciNetCrossRefGoogle Scholar
  42. 42.
    Ge A, Zhang J, Zhang R, Ma C, Zhang Z (2013) Security analysis of a privacy-preserving decentralized key-policy attribute-based encryption scheme. IEEE Trans Parallel Distrib Syst 24(11):2319–2321CrossRefGoogle Scholar
  43. 43.
    Zhang Y, Zhang LY (2015) Exploiting random convolution and random subsampling for image encryption and compression. Electron Lett 51(20):1572–1574CrossRefGoogle Scholar
  44. 44.
    Jolfaei A, Wu XW, Muthukkumarasamy V (2016) On the security of permutation-only image encryption schemes. IEEE Trans Inf Forensics Secur 11(2):235–246CrossRefGoogle Scholar
  45. 45.
    Elshamy AM et al (2013) Optical image encryption based on chaotic baker map and double random phase encoding. J Lightwave Technol 31(15):2533–2539CrossRefGoogle Scholar
  46. 46.
    Cheng H, Li X (2000) Partial encryption of compressed images and videos. IEEE Trans Signal Process 48(8):2439–2451CrossRefGoogle Scholar
  47. 47.
    Abd-El-Hafiz SK, Radwan AG, Abdel Haleem SH, Barakat ML (2014) A fractal-based image encryption system. IET Image Proc 8(12):742–752CrossRefGoogle Scholar
  48. 48.
    Zhou J, Liu X, Au OC, Tang YY (2014) Designing an efficient image encryption-then-compression system via prediction error clustering and random permutation. IEEE Trans Inf Forensics Secur 9(1):39–50CrossRefGoogle Scholar
  49. 49.
    Abdullah AH, Enayatifar R, Leeb M (2012) A hybrid genetic algorithm and chaotic function model for image encryption. Int J Electron Commun (AEU) 66:806–816CrossRefGoogle Scholar
  50. 50.
    Enayatifar R, Abdullah AH, FauziIsnin I (2014) Chaos-based image encryption using a hybrid genetic algorithm and aDNAsequence. Opt Lasers Eng 56:83–93CrossRefGoogle Scholar
  51. 51.
    Wang X, Xu D (2014) Image encryption using genetic operators and intertwining logistic map. Nonlinear Dyn 78(4):2975–2984MathSciNetCrossRefGoogle Scholar
  52. 52.
    Pareek NK, Patidar V (2016) Medical image protection using genetic algorithm operations. Soft Comput 20(2):763–772CrossRefGoogle Scholar
  53. 53.
    Das S, Mandal S, Ghoshal N (2015) Multiple-image encryption using genetic algorithm. Intell Comput Appl 343:145–153Google Scholar
  54. 54.
    Shankar K, Eswaran P (2016) An efficient image encryption technique based on optimized key generation in ECC using genetic algorithm. Artif Intell Evol Comput Eng Syst 394:705–714Google Scholar
  55. 55.
    Su Y, Tang C, Chen X, Li B, Xu W, Lei Z (2017) Cascaded Fresnel holographic image encryption scheme based on a constrained optimization algorithm and Henon map. Opt Lasers Eng 88:20–27CrossRefGoogle Scholar
  56. 56.
    Zhang W, Wang H, Hou D, Yu N (2016) Reversible data hiding in encrypted images by reversible image transformation. IEEE Trans Multimed 18(8):1469–1479CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Information Technology and EngineeringVIT UniversityVelloreIndia
  2. 2.VIT UniversityVelloreIndia

Personalised recommendations