Visual Encryption Using Bit Shift Technique
Keywords:
Cryptography, Matrix Algorithms, Scrambling, Vertical CorrelationAbstract
In present paper we report an effective method of scrambling an image, which can be used as one of the important tool in visual cryptography. A sample image is scrambled using bit shift technique using specific algorithm. The considered algorithm was explained using a matrix representation, taking an 8 x 8 sample matrix. Intensity distribution and toner distributions of scrambled images were studied using their histograms. The results of histogram of an image, in which, each pixel was shifted 4 places left, using bit shift technique, expressed that the toner distribution is uniform throughout. In order to judge the complexity level of scrambling, horizontal and vertical correlation of adjacent pixels and of 4 bit shifted scrambled images were also calculated. Values of horizontal and vertical correlation coefficients were also calculated, which reflected that the complexity and randomness of pixels increases with increasing stages of scrambling which supports the result obtained in histogram. This technique of encryption can be used as a very useful tool in digital security system.
References
X. Chai, Z. Gan, Y. Change, Y. Zang, “A visually secure image encryption scheme based on compressive sensing”, Signal Processing, Vol. 134, Issue.5, pp. 35-51, 2017.
Y. Zang, L.Y. Zhang, “Exploiting random convolution and random subsampling for image encryption and compression”, Electron Letters, Vol. 51, Issue. 20, pp. 1572-1574, 2017.
Z. Hua, Y. Zhou, “Design of image cipher using block-based scrambling and image filtering”, Information Science Vol. 396, Issue.7, pp. 97-113, 2017.
C. Ling, X. Wu, S. Sun, “A general efficient method for chaotic signal estimation”, Transactions on Signal Processing, Vol. 47, Issue. 5, pp. 1424–1428, 1999.
T. Guo, F. Liu, C. Wu, “k out of k extended visual cryptography scheme by random grids”, Signal Processing, Vol. 94, Issue.1, pp. 90-101, 2014.
H.B. Kekre, T. Sarode, P. Halrnkar, “Image scrambling using R-Prime shuffle”, International Journal of Advanced Research in Electrical Electronics and Instrumentation Engineering, Vol. 2, Issue. 8, pp. 4070-4075, 2013.
G. Ye, “Image scrambling encryption algorithm of pixel bit based on chaos map”, Pattern Recognition Letters, Vol. 31, Issue.5, pp. 347–354, 2010.
X. Y. Wang, Y.Q Zhang, L.T. Liu, “An enhanced sub-image encryption method Optics and Lasers in Engineering”, Optics and Laser in Engineering, Vol.86, Issue.11, pp. 248-254, 2016.
A. Soleymani, M. J. Nordin, and E. Sundararajan, “A Chaotic Cryptosystem for Images Based on Henon and Arnold Cat Map”, The Scientific World Journal, vol. 2014, Issue.7, pp. 1-21, 2014.
B. Saha, “A Comparative Analysis of Histogram Equalization Based Image Enhancement Technique for Brightness Preservation”, International Journal of Scientific Research in Computer Science and Engineering, Vol. 3, Issue. 3, pp. 1-5, 2015.
C. P. Patidar and Meena Sharma, "Histogram Computations on GPUs Kernel using Global and Shared Memory Atomics", International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.4, pp.1-6, 2013.
C. Li, K. T. Lo, “Optimal quantitative cryptanalysis of permutation-only multimedia ciphers against plaintext attacks”, Signal Processing, Vol. 91, Issue. 4, pp. 949–954, 2011.
X. Liao, S. Lai, Q. Zhou, “A novel image encryption algorithm based on self-adaptive wave transmission”, Signal Processing, Vol. 90, Issue. 9, pp. 2714–2722, 2010.
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