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A Systematic Review of Metaheuristic-based Image Encryption Techniques

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Abstract

Image encryption protects the sensitive and confidential information of images. This protection comes from the combination of secret keys, encryption, and decryption algorithms. Chaotic maps are widely utilized by researchers to perform image encryption. Encryption with chaotic maps is very sensitive to initial conditions. Therefore, it can produce unacceptably low performance if the input parameters are not chosen wisely. This problem is solved by using meta-heuristic techniques in image encryption to obtain the optimized initial conditions. This paper presents a systematic review of metaheuristic algorithms used for image encryption. In this study, an effort is made to highlight the features and different issues of existing metaheuristic-based image encryption techniques. Parallel implementation, Hyper-parameter tuning, Stuck in local optima, Premature convergence, and Computational speed methods are generally used to evaluate metaheuristic-based image encryption techniques. The security parameters of these techniques, such as key space, speed, entropy, Number of Pixel Change Rate, Unified Average Changing Intensity, and correlation coefficient, are also evaluated. Articles from various databases are taken for study. In this systematic review, various research questions are identified and based on their answers, results have been formulated. Based on the study, the future directions are also identified for coming researchers in the field of metaheuristic-based image encryption.

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References

  1. Coppersmith D (1994) The data encryption standard (DES) and its strength against attacks. IBM J Res Dev 38(3):243–250

    MATH  Google Scholar 

  2. NIST (2001) Advanced Encryption Standard (AES). Federal Information Processing Standards Publication 197, 0311

  3. Gao H, Zhang Y, Liang S, Li D (2006) A new chaotic algorithm for image encryption. Chaos Solitons Fractals 29(2):393–399. https://doi.org/10.1016/j.chaos.2005.08.110

    Article  MATH  Google Scholar 

  4. Samhita P, Prasad P, Patro KAK, Acharya B (2016) A secure chaos-based image encryption and decryption using crossover and mutation operator. Int J Control Theory Appl 9(34):17–28

    Google Scholar 

  5. Gupta A, Thawait R, Patro KAK, Acharya B (2016) A novel image encryption based on bit-shuffled improved tent map. Int J Control Theory Appl 9(34):1–16

    Google Scholar 

  6. Shadangi V, Choudhary SK, Patro KAK, Acharya B (2017) Novel arnold scrambling based CBC-AES image encryption. Int J Control Theory Appl 10(15):93–105

    Google Scholar 

  7. Guesmi R, Farah MAB, Kachouri A, Samet M (2016) Hash key-based image encryption using crossover operator and chaos. Multimed Tools Appl 75(8):4753–4769. https://doi.org/10.1007/s11042-015-2501-0

    Article  MATH  Google Scholar 

  8. Guesmi R, Farah M, Kachouri A, Samet M (2016) A novel chaos-based image encryption using DNA sequence operation and secure hash algorithm SHA-2. Nonlinear Dyn 83(3):1123–1136. https://doi.org/10.1007/s11071-015-2392-7

    Article  MathSciNet  MATH  Google Scholar 

  9. Matthews R (1989) On the derivation of a ǣchaoticǥ encryption algorithm. Cryptologia 13(1):29–42

    MathSciNet  Google Scholar 

  10. Liu W, Sun K, Zhu C (2016) A fast image encryption algorithm based on chaotic map. Opt Lasers Eng 84:26–36

    Google Scholar 

  11. Wang X, Wang S, Zhang Y, Guo K (2017) A novel image encryption algorithm based on chaotic shuffling method. Inf Secur J A Glob Perspect 26(1):7–16

    Google Scholar 

  12. Li C, Luo G, Qin K, Li C (2017) An image encryption scheme based on chaotic tent map. Nonlinear Dyn 87(1):127–133

    Google Scholar 

  13. Chai X-L, Gan Z-H, Lu Y, Zhang M-H, Chen Y-R (2016) A novel color image encryption algorithm based on genetic recombination and the four-dimensional memristive hyperchaotic system. Chinese Phys B 25(10):100503

    Google Scholar 

  14. Mozaffari S (2018) Parallel image encryption with bitplane decomposition and genetic algorithm. Multimed Tools Appl 77(19):25799–25819

    Google Scholar 

  15. Liu H, Zhao B, Huang L (2019) A novel quantum image encryption algorithm based on crossover operation and mutation operation. Multimed Tools Appl 78(14):20465–20483

    Google Scholar 

  16. Talarposhti KM, Jamei MK (2016) A secure image encryption method based on dynamic harmony search (DHS) combined with chaotic map. Opt Lasers Eng 81:21–34

    Google Scholar 

  17. Kaur M, Kumar V (2018) Parallel non-dominated sorting genetic algorithm-II-based image encryption technique. IMAGING Sci J 66(8):453–462

    Google Scholar 

  18. Ghazvin M, Mirzad M, Parvar N (2020) A modified method for image encryption basedon chaotic map and genetic algorithm. Multimed Tools Appl. https://doi.org/10.1007/s11042-020-09058-3

    Article  Google Scholar 

  19. Chikkareddi V, Ghosh A, Jagtap P, Joshi S, Kanzaria J (2020) Hybrid image encryption technique using Genetic algorithm and Lorenz Chaotic system. ITM Web of Conferences 32, 03009. ICACC-2020

  20. Niu Y, Zhou Z, Zhang X (2020) An image encryption approach based on chaotic maps and genetic operations. Multimed Tools Appl. https://doi.org/10.1007/s11042-020-09237-2

    Article  Google Scholar 

  21. Kaur M, Kumar V (2018) Fourier-Mellin moment-based intertwining map for image encryption. Mod Phys Lett B 32(9):1850115

    MathSciNet  Google Scholar 

  22. Enayatifar R, Abdullah AH, Isnin IF (2014) Chaos-based image encryption using a hybrid genetic algorithm and a DNA sequence. Opt Lasers Eng 56:83–93

    Google Scholar 

  23. Kitchenham B (2007) Charters. Guidelines for performing systematic literature review in software engineering. Keele, UK, Keele University Version 2.3

  24. Su Y, Tang C, Chen X et al (2017) Cascaded Fresnel holographic image encryption scheme based on a constrained optimization algorithm and henon map. Opt Lasers Eng. https://doi.org/10.1016/j.optlaseng.2016.07.012

    Article  Google Scholar 

  25. Noshadian S, Ebrahimzade A, Kazemitabar S (2018) Optimizing chaos based image encryption. Multimed Tools Appl. https://doi.org/10.1007/s11042-018-5807-x

    Article  Google Scholar 

  26. Kaur M, Singh D (2020) Multiobjective evolutionary optimization techniques based hyperchaotic map and their applications in image encryption. Multidimension Syst Signal Process. https://doi.org/10.1007/s11045-020-00739-8

    Article  MATH  Google Scholar 

  27. Abdullah AH, Enayatifar R, Lee M (2012) A hybrid genetic algorithm and chaotic function model for image encryption, AEU – Int. J Electron Commun 66(10):806–816

    Google Scholar 

  28. Yang F, Mou J, Luo C, Cao Y (2019) An improved color image encryption scheme and cryptanalysis based on a hyperchaotic sequence. Phys Scr 94(8):085206

    Google Scholar 

  29. Wu T-Y, Fan X, Wang K-H, Pan J-S, Chen C-M (2019) Security analysis and improvement on an image encryption algorithm using chebyshev generator. J INTERNET Technol 20(1):13–23

    Google Scholar 

  30. Mashwani WK, Shah SNA, Belhaouari SB, Hamdi A (2021) Ameliorated ensemble strategy-based evolutionary algorithm with dynamic resources allocations. Int J Comput Intell Syst 14(1):412–437

    Google Scholar 

  31. Mashwani WK, Hamdi A, Asif Jan M, Göktaş A, Khan F (2020) Large-scale global optimization based on hybrid swarm intelligence algorithm. J Intell Fuzzy Syst 39(1):1257–1275

    Google Scholar 

  32. Mashwani WK, Haider R, Brahim Belhaouari S (2021) A multiswarm intelligence algorithm for expensive bound constrained optimization problems. Complexity 2021:1–18

    Google Scholar 

  33. Mashwani WK, Rehman ZU, Bakar MA, Koçak I, Fayaz M (2021) A customized differential evolutionary algorithm for bounded constrained optimization problems. Complexity 2021:1–24

    Google Scholar 

  34. Mashwani WK, Khan A, Göktaş A, Unvan YA, Yaniay O, Hamdi A (2021) Hybrid differential evolutionary strawberry algorithm for real-parameter optimization problems. Commun Stat-Theory Methods 50(7):1685–1698

    MathSciNet  MATH  Google Scholar 

  35. Mashwani WK, Mehmood I, Abu Bakar M, Koçcak I (2021) A modified bat algorithm for solving large-scale bound constrained global optimization problems. Math Problems Eng 2021:1–14

    Google Scholar 

  36. McCall J (2005) Genetic algorithms for modelling and optimisation. J Comput Appl Math 184(1):205–222

    MathSciNet  MATH  Google Scholar 

  37. Muhammad ASIM, Khan WM, Yeniay Ö, Jan MA, Tairan N, Hussian H, Wang GG (2018) Hybrid genetic algorithms for global optimization problems. Hacettepe J Math Stat 47(3):539–551

    MathSciNet  MATH  Google Scholar 

  38. Yaghouti Niyat A, Moattar MH (2020) Color image encryption based on hybrid chaotic system and DNA sequences. Multimed Tools Appl 79:1497–1518. https://doi.org/10.1007/s11042-019-08247-z

    Article  Google Scholar 

  39. Sreelaja N, Pai G (2012) Stream cipher for binary image encryption using Ant Colony Optimization based key generation. Appl Soft Comput 12(9):2879–2895

    Google Scholar 

  40. Zhang X, Wang X, Cheng Y (2015) Image encryption based on a genetic algorithm and a chaotic system. IEICE Trans Commun E98B(5):824–833

    Google Scholar 

  41. Wang X, Zhang H (2016) A novel image encryption algorithm based on genetic recombination and hyper-chaotic systems. NONLINEAR Dyn 83(1–2):333–346

    MathSciNet  Google Scholar 

  42. Ahmad M, Alam M, Umayya Z, Khan S, Ahmad F (2018) An image encryption approach using particle swarm optimization and chaotic map. Int J Inf technol. https://doi.org/10.1007/s41870-018-0099-y

    Article  Google Scholar 

  43. Shankar K, Mohamed E, Eswaran P, Llayaraja M, Sathesh Kumar K (2019) An efficient image encryption schemw based on signcryption technique with adaptive elephant herding optimization. Inf Syst. https://doi.org/10.1007/978-3-030-16837-7_3

    Article  Google Scholar 

  44. Kaur M, Kumar V (2018) Beta chaotic map based image encryption using genetic algorithm. Int J Bifurc CHAOS 28(11):1850132

    MathSciNet  MATH  Google Scholar 

  45. Nematzadeh H, Enayatifar R, Motameni H, Guimaraes FG, Coelho VN (2018) Medical image encryption using a hybrid model of modified genetic algorithm and coupled map lattices. Opt Lasers Eng 110:24–32

    Google Scholar 

  46. Premkumar R, Anand S (2019) Secured and compound 3-D chaos image encryption using hybrid mutation and crossover operator. Multimed Tools Appl 78(8):9577–9593

    Google Scholar 

  47. Kaur M, Kumar V (2018) Adaptive differential evolution-based Lorenz chaotic system for image encryption. Arab J Sci Eng 43(12):8127–8144

    Google Scholar 

  48. Gupta A, Singh D, Kaur M (2020) An efficient image encryption using non-dominated sorting genetic algorithm-iii based 4-d chaotic maps. J Ambient Intell Humaniz Comput 11(3):1309–1324

    Google Scholar 

  49. Kaur M, Singh D, Sun K, Rawat U (2020) Color image encryption using non-dominated sorting genetic algorithm with local chaotic search based 5D chaotic map. Fut Gener Comput Syst 107:333–350

    Google Scholar 

  50. Enayatifar R, Abdullah AH, Lee M (2013) A weighted discrete imperialist competitive algorithm (WDICA) combined with chaotic map for image encryption. Opt Lasers Eng 51(9):1066–1077

    Google Scholar 

  51. Kaur M, Singh D, Uppal RS (2019) Parallel strength pareto evolutionary algorithm- II based image encryption. IET Image Process 14(6):1015–1026

    Google Scholar 

  52. Shankar K, Eswaran .P (2016) An efficient image encryption based on optimization key generation in ECC using genetic algorithm. In Artificial intelligence and evolutionary computation in engineering system

  53. Abbasi AA, Mazinani M, Hosseini R (2020) Evolutionary based image encryption using biomolecules operators and non –coupled map lattice. Opitik 219:164949

    Google Scholar 

  54. Krishna GJ, Ravi V, Bhattu SN (2018) key generation for plain text in stream cipher via bi-objective evolutionary computing. Appl Soft Comput 70:301–317

    Google Scholar 

  55. Mondal B, Mandal T (2019) A secure image encryption scheme based on genetic operations and a new hybrid pseudo random number generator. Multimed Tools Appl. https://doi.org/10.1007/s11042-019-08352-z

    Article  Google Scholar 

  56. Mahmud M, Atta-ur-Rahman ML, Choi J-Y (2020) Evolutionary-based image encryption using RNA codons truth table. Opt LASER Technol 121:105818

    Google Scholar 

  57. Kaur M, Singh D, Kumar V (2020) Color image encryption using minimax differential evolution-based 7D hyper-chaotic map. Appl Phys B 126(9):1–19

    Google Scholar 

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Correspondence to Dilbag Singh.

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Kaur, M., Singh, S., Kaur, M. et al. A Systematic Review of Metaheuristic-based Image Encryption Techniques. Arch Computat Methods Eng 29, 2563–2577 (2022). https://doi.org/10.1007/s11831-021-09656-w

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