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Remodeling randomness prioritization to boost-up security of RGB image encryption

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Abstract

Securing information became essential to exchange multimedia information safely. The exchanged data need to be transformed in a well-managed, secure, and reliable manner. In this paper, we will focus on securing RGB images via cryptography during transmission among users using our effective proposal of utilizing appropriate Pseudo Random Number Generator (PRNG). We implement many techniques of PRNG involved in two consecutive crypto-processes of substitution and transposition to present secure image transformation. Our technique proposal of PRNGs selection is based on testing to encrypt RGB images to be compared with current related used approaches. The work experimentation aims to identify suitability and reliability through security measures standard parameters. The research justifies its proper PRNG selection to model our approach as attractive effective work worth remarking.

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References

  1. Abbas NA (2016) Image encryption based on independent component analysis and Arnold’s cat map. Egypt Inform J 17(1):139–146

    Article  Google Scholar 

  2. Ahmad J, Hwang SO (2016) A secure image encryption scheme based on chaotic maps and affine transformation. Multimed Tools Appl 75(21):13951–13976

    Article  Google Scholar 

  3. Alharthi N, Gutub A (2017) Data visualization to explore improving decision-making within hajj services. Sci Model Res 2(1):9–18

    Google Scholar 

  4. Al-Juaid N, Gutub A (2019) Combining RSA and audio steganography on personal computers for enhancing security. SN Appl Sci 1(8):830

    Article  Google Scholar 

  5. AlKhodaidi T, Gutub A (2020) Trustworthy target key alteration helping counting-based secret sharing applicability. Arab J Sci Eng:1–21

  6. Al-Najjar Y, Soong D (2012) Comparison of image quality assessment: PSNR, HVS, SSIM, UIQI. Int J Sci Eng Res 3(8):1–5

    Google Scholar 

  7. Al-Otaibi N, Gutub A (2014) 2-leyer security system for hiding sensitive text data on personal computers. Lect Notes Inf Theory 2(2):151–157

    Google Scholar 

  8. Altalhi S, Gutub A (2021) A survey on predictions of cyber-attacks utilizing real-time twitter tracing recognition. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-020-02789-z

  9. An Enhanced Least Significant Bit Steganography Technique. (2016)

  10. Andreatos AS, Leros AP (2014) A comparison of random number sequences for image encryption. Proceedings of MMCTSE, Mathematical Methods & Computational Techniques in Science & Engineering. Athens, Greece, p. 146–151

  11. Anley C (2007) Weak randomness: part I—linear congruential random number generators. Next Generation Security Software

  12. Ayushi A (2010) Symmetric key cryptographic algorithm. Int J Comput Appl 1(15):1–2

    Google Scholar 

  13. Bani MA, Jantan A (2008) Image encryption using block-based transformation algorithm. IJCSNS Int J Comput Sci Netw Secur 8(4):191–197

    Google Scholar 

  14. Banthia AK, Tiwari N (2013) Image encryption using Pseudo random number generators. Int J Comput Appl 975:8887

    Google Scholar 

  15. Bassham III LE, et al. (2010) Sp 800–22 rev. 1a. a statistical test suite for random and pseudorandom number generators for cryptographic applications. National Institute of Standards & Technology

  16. Batool SI, Shah T, Khan M (2014) A color image watermarking scheme based on affine transformation and S 4 permutation. Neural Comput & Applic 25(7–8):2037–2045

    Article  Google Scholar 

  17. Behnia S et al (2013) Image encryption based on the Jacobian elliptic maps. J Syst Softw 86(9):2429–2438

    Article  Google Scholar 

  18. Bhattacharjee K, Maity K, Das S (2018) A search for good pseudo-random number generators: Survey and empirical studies. arXiv preprint arXiv:1811.04035

  19. Chen X, Hu C-J (2017) Medical image encryption based on multiple chaotic mapping and wavelet transform

  20. Ding W (2001) Digital image scrambling technology based on Arnold transformation. J Comput Aided Des Comput Graph 13(4):338–341

    Google Scholar 

  21. Easttom C (2017) Generating Cryptographic Keys: Will Your Random Number Generators (PRNGs) Do The Job? 22. Available from: https://www.cryptomathic.com/news-events/blog/generating-cryptographic-keys-with-random-number-generators-prng.

  22. Elsayed M et al A new method for full reference image blur measure. Int J Simul Syst Sci Technol 19:4

  23. Eskicioglu A, Fisher P (1995) Image quality measures and their performance. IEEE Trans Commun 43(12):2959–2965

    Article  Google Scholar 

  24. Fathi-Vajargah B, Kanafchian M, Alexandrov V (2018) Image encryption based on permutation and substitution using Clifford chaotic system and logistic map. J Comput 13(3):309–326

    Article  Google Scholar 

  25. Francois M et al (2013) A new pseudo-random number generator based on two chaotic maps. Informatica 24(2):181–197

    Article  MathSciNet  MATH  Google Scholar 

  26. Fridrich J (1997) Image encryption based on chaotic maps. In 1997 IEEE international conference on systems, man, and cybernetics. Computational cybernetics and simulation. IEEE

  27. Galajda MDP (2006) Chaos-based true random number generator embedded in a mixed-signal reconfigurable hardware. J Electr Eng 57(4):218–225

    Google Scholar 

  28. Gao T, Chen Z (2008) Image encryption based on a new total shuffling algorithm. Chaos, Solitons Fractals 38(1):213–220

    Article  MathSciNet  MATH  Google Scholar 

  29. Gashim LL, Hussein KQ (2018) A new algorithm of encryption and decryption of image using combine chaotic mapping. Iraqi J Inf Technol 9(2 اللغة الانكليزية): 1–16. https://www.iasj.net/iasj/article/153322

  30. Gutub A (2011) Subthreshold sram designs for cryptography security computations. In: International Conference on Software Engineering and Computer Systems. Springer

  31. Gutub A, Tenca A (2004) Efficient scalable VLSI architecture for Montgomery inversion in GF (p). Integr VLSI J 37(2):103–120

    Article  Google Scholar 

  32. Gutub A, Al-Juaid N, Khan E (2019) Counting-based secret sharing technique for multimedia applications. Multimed Tools Appl 78(5):5591–5619

    Article  Google Scholar 

  33. Haahr M (n.d.) Introduction to Randomness and Random Numbers. Available from: https://www.random.org/randomness/

  34. Hassan M, Bhagvati C (2012) Structural similarity measure for color images. Int J Comput Appl 43(14):7–12

    Google Scholar 

  35. Hussain I, Gondal MA (2014) An extended image encryption using chaotic coupled map and S-box transformation. Nonlinear Dyn 76(2):1355–1363

    Article  Google Scholar 

  36. Jagalingam P, Hegde A (2015) A review of quality metrics for fused image. Aquat Procedia 4(Icwrcoe):133–142

    Article  Google Scholar 

  37. Janke W (2002) Pseudo random numbers: generation and quality checks. Lect Notes John von Neumann Inst Comput 10:447

    Google Scholar 

  38. Kapur V, Paladi ST, Dubbakula N (2015) Two level image encryption using pseudo random number generators. Int J Comput Appl 115:12

    Google Scholar 

  39. Kelsey J, et al. (1998) Cryptanalytic attacks on pseudorandom number generators. In International workshop on fast software encryption. Springer

  40. Kuo C-J (n.d.) E-mail: jimkuo@ aa. Nctu. Edu. Tw graduate Institute of Communication Engineering National Taiwan University, Taipei, Taiwan, ROC

  41. L'Ecuyer P (1999) Good Parameter Sets for Combined Multiple Recursive Random Number Generators ІІ Shorter Version in Operations Research, V. 47І1. P. 159Ä164

  42. Li TY, Yorke JA (1975) Period three implies chaos. Am Math Mon 82(1):975

    MathSciNet  MATH  Google Scholar 

  43. 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 

  44. Mao Y, Chen G, Lian S (2004) A novel fast image encryption scheme based on 3D chaotic baker maps. Int J Bifurcation Chaos 14(10):3613–3624

    Article  MathSciNet  MATH  Google Scholar 

  45. Marsaglia G, Tsang WW (2000) The ziggurat method for generating random variables. J Stat Softw 5(8):1–7

    Article  Google Scholar 

  46. Marsaglia G, Zaman A (1991) A new class of random number generators. Ann Appl Probab 1(3):462–480

    Article  MathSciNet  MATH  Google Scholar 

  47. Mascagni M, Srinivasan A (2004) Parameterizing parallel multiplicative lagged-Fibonacci generators. Parallel Comput 30(7):899–916

    Article  MathSciNet  Google Scholar 

  48. Matsumoto M, Nishimura T (1998) Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator. ACM Trans Model Comput Simul (TOMACS) 8(1):3–30

    Article  MATH  Google Scholar 

  49. Mitra A, Rao YS, Prasanna S (2006) A new image encryption approach using combinational permutation techniques. Int J Comput Sci 1(2):127–131

    Google Scholar 

  50. Murillo-Escobar M et al (2017) A novel pseudorandom number generator based on pseudorandomly enhanced logistic map. Nonlinear Dyn 87(1):407–425. https://doi.org/10.1007/s11071-016-3051-3

  51. Norouzi B et al (2015) A novel image encryption based on row-column, masking and main diffusion processes with hyper chaos. Multimed Tools Appl 74(3):781–811

    Article  Google Scholar 

  52. Pak C, Huang L (2017) A new color image encryption using combination of the 1D chaotic map. Signal Process 138:129–137

    Article  Google Scholar 

  53. Patidar V, Sud K (2009) A novel pseudo random bit generator based on chaotic standard map and its testing. Electron J Theor Phys 6(20):327–344

    Google Scholar 

  54. Peterson G (1997) Arnold’s cat map. Math Linear Algebra 45:1–7

    Google Scholar 

  55. Petronas U (2011) Mean and standard deviation features of color histogramusing laplacian filter for content-based image retrieval. J Theor Appl Inf Technol 34(1):1–7

    Google Scholar 

  56. Preiss J (2015) Color-image quality assessment: from metric to application. PhD Thesis at Technische Universität. https://tuprints.ulb.tudarmstadt.de/4389/1/Preiss_PhD-Thesis.pdf (Accessed June 2021)

  57. Pu C (2015) Image scrambling algorithm based on image block and zigzag transformation. Comput Model New Technol:489–493

  58. Rajkumar S, Malathi G (2016) A comparative analysis on image quality assessment for real time satellite images. Indian J Sci Technol 9:34

    Article  Google Scholar 

  59. Ramasamy P et al (2019) An image encryption scheme based on block scrambling, modified zigzag transformation and key generation using enhanced logistic—tent map. Entropy 21(7):656

    Article  MathSciNet  Google Scholar 

  60. Ramesh A, Jain A (2015) Hybrid image encryption using Pseudo Random Number Generators, and transposition and substitution techniques. In: 2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15). IEEE.

  61. Rohith S, Bhat KH, Sharma AN (2014) Image encryption and decryption using chaotic key sequence generated by sequence of logistic map and sequence of states of Linear Feedback Shift Register. In: 2014 International Conference on Advances in Electronics Computers and Communications. IEEE

  62. Rukhin A, et al. (2001) A statistical test suite for random and pseudorandom number generators for cryptographic applications. Booz-allen and hamilton inc mclean va

  63. Saha S, Karsh R, Amrohi M (2018) Encryption and decryption of images using secure linear feedback shift registers. IEEE: International Conference on Communication and Signal Processing (ICCSP)

  64. Saito M, Matsumoto M (2009) A PRNG specialized in double precision floating point numbers using an affine transition, in Monte Carlo and Quasi-Monte Carlo Methods 2008 (p. 589–602). Springer

  65. Sang J et al (2018) Joint image compression and encryption using IWT with SPIHT, Kd-tree and chaotic maps. Appl Sci 8(10):1963

    Article  Google Scholar 

  66. Saputra I (2017) Image scrambling using one time pad with linear congruent key generator. IJICS Int J Inf Comput Sci 1(1)

  67. Sarma K, Lavanya B (2017) Digital image scrambling based on sequence generation. In: 2017 International Conference on Circuit, Power and Computing Technologies (ICCPCT). IEEE

  68. Savvidy KG (2015) The MIXMAX random number generator. Comput Phys Commun 196:161–165

    Article  MATH  Google Scholar 

  69. Shanon C (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–623

    Article  MathSciNet  Google Scholar 

  70. Shure SEaL (2001) Matrix Indexing in MATLAB. Available from: https://www.mathworks.com/company/newsletters/articles/matrix-indexing-in-matlab.html

  71. Sivakumar T, Devi KG (2017) Image encryption using block permutation and XOR operation. Int J Comput Appl 975:8887

    Google Scholar 

  72. Som S, et al. (2014) A chaos based partial image encryption scheme. In: 2014 2nd International Conference on Business and Information Management (ICBIM). IEEE

  73. Stallings W (2003) Cryptography and network security: principles and practices,‖ prentice hall. Upper Saddle River

  74. Stinson DR, Paterson M (2018) Cryptography: theory and practice. CRC Press.

  75. The USC-SIPI Image Database. (n.d.) Available from: http://sipi.usc.edu/database/database.php.

  76. Tomassini M, Perrenoud M (2001) Cryptography with cellular automata. Appl Soft Comput 1(2):151–160

    Article  MATH  Google Scholar 

  77. Al-Roithy B, Gutub A (2020) Trustworthy image security via involving binary and chaotic gravitational searching within PRNG selections. International Journal of Computer Science and Network Security (IJCSNS) 20(12):167–176. https://doi.org/10.22937/IJCSNS.2020.20.12.18

  78. Wang Z, Bovik AC (2002) A universal image quality index. IEEE Signal Proc Lett 9(3):81–84

    Article  Google Scholar 

  79. Wang Z, Simoncelli EP, Bovik AC (2003) Multiscale structural similarity for image quality assessment. In: The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003. IEEE

  80. Wu Y, Noonan J, Agaian S, NPCR and UACI randomness tests for image encryption (2011) Cyber journals: multidisciplinary journals in science and technology. J Sel Areas Telecommun (JSAT) 1(2):31–38

    Google Scholar 

  81. Wu Y, Noonan JP, Agaian S (2011) Shannon entropy based randomness measurement and test for image encryption. arXiv preprint arXiv:1103.5520

  82. Yang Y-G, Zhao Q-Q (2016) Novel pseudo-random number generator based on quantum random walks. Sci Rep 6(1):1–11

    MathSciNet  Google Scholar 

  83. Yang Y-G et al (2019) Image compression-encryption scheme based on fractional order hyper-chaotic systems combined with 2D compressed sensing and DNA encoding. Opt Laser Technol 119:105661

    Article  Google Scholar 

  84. Ye H-S, Zhou N-R, Gong L-H (2020) Multi-image compression-encryption scheme based on quaternion discrete fractional Hartley transform and improved pixel adaptive diffusion. Signal Process 175:107652

    Article  Google Scholar 

  85. Yen K, Yen EK, Johnston RG (1996) The ineffectiveness of the correlation coefficient for image comparisons

  86. Younas I, Khan M (2018) A new efficient digital image encryption based on inverse left almost semi group and Lorenz chaotic system. Entropy 20(12):913

    Article  Google Scholar 

  87. Yu S-S et al (2020) Optical image encryption algorithm based on phase-truncated short-time fractional Fourier transform and hyper-chaotic system. Opt Lasers Eng 124:105816

    Article  Google Scholar 

  88. Zhang L, Tian X, Xia S (2011) A scrambling algorithm of image encryption based on Rubik's cube rotation and logistic sequence. In: 2011 International Conference on Multimedia and Signal Processing. IEEE.

  89. Zhang Q, Xue X, Wei X (2012) A novel image encryption algorithm based on DNA subsequence operation. Sci World J 2012

  90. Zheng F et al (2008) Pseudo-random sequence generator based on the generalized Henon map. J China Univ Posts Telecommun 15(3):64–68

    Article  Google Scholar 

  91. Zhou Q et al (2008) Parallel image encryption algorithm based on discretized chaotic map. Chaos, Solitons Fractals 38(4):1081–1092

    Article  Google Scholar 

  92. Zhou NR et al (2015) Quantum image encryption based on generalized Arnold transform and double random-phase encoding. Quantum Inf Process 14(4):1193–1213

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgments

This work has been supported by Umm Al-Qura University. We thank our college of computer and information system for providing assistance to make this research possible.

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Correspondence to Adnan Gutub.

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Al-Roithy, B.O., Gutub, A. Remodeling randomness prioritization to boost-up security of RGB image encryption. Multimed Tools Appl 80, 28521–28581 (2021). https://doi.org/10.1007/s11042-021-11051-3

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