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Home»Articles»Visual Encryption Using Multilevel Scrambling Followed by Affine Encryption Technique

Visual Encryption Using Multilevel Scrambling Followed by Affine Encryption Technique

Author : Piyali Sharma, Pramay Bhatpahri, Ravi Kiran Patnaik and Ravi Shrivastava
Volume 7 No.1 January-June 2018 pp 40-45

Abstract

In the present paper, we report an effective method of multilevel scrambling followed by affine encryption, which may be used as one of the useful tools in visual cryptography. A sample image is scrambled for six times using a specific algorithm. Toner distributions of scrambled images were studied using their histograms. The results of histogram expressed that the effectiveness of scrambling increased with its increasing stages and it becomes almost ideal when the image after affine encryption is taken. In order to judge the complexity level of scrambling, horizontal & vertical correlation of adjacent pixels and Information Entropy of different scrambled images were also calculated. Values of horizontal & vertical correlation and information entropy reflected that the complexity and randomness of pixels increase with increasing stages of scrambling. It also indicated that the randomness doesn’t change much after the fifth stage of scrambling and affine encryption enhanced the level of security by a large extent.

Keywords

Cryptography, Matrix algorithms, Scrambling, Horizontal Correlation, Vertical Correlation

Full Text:

References

[1] H. Zhua, C. Zhao, X. Zhanga, and L. Yang, “An image encryption scheme using generalized Arnold map and affine cipher”, Optik, Vol. 125 No. 22, pp. 6672-6677, November 2014.
[2] R. Z. Wang, Y. C. Lana, Y. K. Lee, S. Y. Huang, S. J. Shyu, and T. L. Chia, “Incrementing visual cryptography using random grids, Optics Communications”, Vol. 283, No. 21, pp. 4242-4249, November 2010.
[3] R. Lukac, K.N. Plataniotis, “Bit-level based secret sharing for image encryption”, Pattern Recognition, Vol. 38, pp. 767-772, May 2005.
[4] M. Naor and B. Pinkas, “Visual authentication and identification, advances in cryptography”, Lecture Notes in Computer Science, Springer-Verlag, New York, Vol. 1294, pp. 322–336, August 1997.
[5] D.C. Lou, H.K. Tso, and J.L. Liu, “A copyright protection scheme for digital images using visual cryptography technique”, Computer Standards and Interfaces, Vol. 29, pp. 125-131, January 2007.
[6] X. Y. Wang, Y.Q Zhang, and L.T. Liu, “An enhanced sub-image encryption method”, Optics and Laser in Engineering, Vol. 86, pp. 248-254, November 2016.
[7] https://en.wikipedia.org/wiki/Image_histogram, (18 April 2017)
[8] C. Li and K. T. Lo, “Optimal quantitative cryptanalysis of permutation-only multimedia ciphers against plaintext attacks”, Signal Process, Vol. 91, No. 4, pp. 949-954, June 2011.
[9] X. Liao, S. Lai, Q. Zhou, “A novel image encryption algorithm based on self-adaptive wave transmission”, Signal Process, Vol. 90, No. 9, pp. 2714-2722, September 2010.
[10] https://en.wikipedia.org/wiki/Image_histogram, accessed on 17 June 2017.
[11] X. Tong, Y. Liu , M. Zhang , H. Xu and Z. Wang, “An Image Encryption Scheme Based on Hyperchaotic Rabinovich and Exponential Chaos Maps”, Entropy, Vol. 17 No. 1, pp. 181-196, January 2015.
[12] B. Stoyanov, and K. Kordov,” Image Encryption Using Chebyshev Map and Rotation Equation”, Entropy, Vol. 17, No. 4, pp. 2117-2139, 2015.
[13] Yue Wu, Student Member, IEEE, Joseph P. Noonan, Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), April Edition, 2011
[14] https://en.wikipedia.org/wiki/Affine_cipher, accessed on 16 June 2017
[15] https://en.wikipedia.org/wiki/Differential_cryptanalysis, accessed on 16 June 2017

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In the present paper, we report an effective method of multilevel scrambling followed by affine encryption, which may be used as one of the useful tools in visual cryptography. A sample image is scrambled for six times using a specific algorithm. Toner distributions of scrambled images were studied using their histograms. The results of histogram expressed that the effectiveness of scrambling increased with its increasing stages and it becomes almost ideal when the image after affine encryption is taken. In order to judge the complexity level of scrambling, horizontal & vertical correlation of adjacent pixels and Information Entropy of different scrambled images were also calculated. Values of horizontal & vertical correlation and information entropy reflected that the complexity and randomness of pixels increase with increasing stages of scrambling. It also indicated that the randomness doesn’t change much after the fifth stage of scrambling and affine encryption enhanced the level of security by a large extent.

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Global Lead, Supply Chain Management, Center of Competence and Senior Knowledge
Expert at McKinsey and Company, India
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Department of Computer Science, Basra University, Iraq
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Dr. Norjihan Binti Abdul Ghani
Department of Information System, University of Malaya, Malaysia
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Dr. Christos Bouras
Department of Computer Engineering & Informatics, University of Patras, Greece
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Dr. Maizatul Akmar Binti Ismail
Department of Information System, University of Malaya, Malaysia
[email protected]
Dr. Harold Castro
Department of Systems Engineering and Computing, University of the Andes, Colombia
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Dr. Busyairah Binti Syd Ali
Department of Software Engineering, University of Malaya, Malaysia
[email protected]
Dr. Sri Devi Ravana
Department of Information system, University of Malaya, Malaysia
[email protected]
Dr. Karpaga Selvi Subramanian
Department of Computer Engineering, Mekelle University, Ethiopia
[email protected]
Dr. Mazliza Binti Othman
Department of Computer System & Technology, University of Malaya, Malaysia
[email protected]
Dr. Chiam Yin Kia
Department of Software Engineering, University of Malaya, Malaysia
[email protected]
Dr. OUH Eng Lieh
Department of Information Systems, Singapore Management University, Singapore
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    Editorial Note

    Editorial Dr. K. Ganesh

    Editor-in-Chief
    Dr. K. Ganesh
    Global Lead, Supply Chain Management, Center of Competence and Senior Knowledge
    Expert at McKinsey and Company, India
    [email protected]
    Editorial Advisory Board
    Dr. Eng. Hamid Ali Abed AL-Asadi
    Department of Computer Science, Basra University, Iraq
    [email protected]
    Dr. Norjihan Binti Abdul Ghani
    Department of Information System, University of Malaya, Malaysia
    [email protected]
    Dr. Christos Bouras
    Department of Computer Engineering & Informatics, University of Patras, Greece
    [email protected]
    Dr. Maizatul Akmar Binti Ismail
    Department of Information System, University of Malaya, Malaysia
    [email protected]
    Dr. Harold Castro
    Department of Systems Engineering and Computing, University of the Andes, Colombia
    [email protected]
    Dr. Busyairah Binti Syd Ali
    Department of Software Engineering, University of Malaya, Malaysia
    [email protected]
    Dr. Sri Devi Ravana
    Department of Information system, University of Malaya, Malaysia
    [email protected]
    Dr. Karpaga Selvi Subramanian
    Department of Computer Engineering, Mekelle University, Ethiopia
    [email protected]
    Dr. Mazliza Binti Othman
    Department of Computer System & Technology, University of Malaya, Malaysia
    [email protected]
    Dr. Chiam Yin Kia
    Department of Software Engineering, University of Malaya, Malaysia
    [email protected]
    Dr. OUH Eng Lieh
    Department of Information Systems, Singapore Management University, Singapore
    [email protected]

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