Visual Encryption Using Block based Scrambling Followed by Affine Encryption Technique
DOI:
https://doi.org/10.32628/CSEIT2174130Keywords:
Scrambling, Visual encryption, Block level encryption.Abstract
This article reports the Block based cipher concept followed by the affine cipher technique. The Image considered was grouped into squared (16, 32 and 64) pixel blocks then each column was shifted by specific values. These values were randomly generated prime numbers and worked as the key for scrambling. These images were investigated for their quality of scrambling using histogram and adjacent pixel correlation. The adjacent pixel correlations for 16, 32 and 64 pixel-based ciphered images were found as 0.7907, 0.7292, and 0.4783 respectively. The analysis gave the information that the level of scrambling was not satisfactory, therefore; the affine cipher technique was applied to each of the images. These images were converted into the matrix format and each element was transformed using the affine cipher. This transformed matrix is again converted inform from the image to visualize. The Histogram and adjacent pixel correction for these images were much improved.
References
- Zhongyun Hua, Yicong Zhou, “Design of image cipher using block-based scrambling and image filtering”, Information Sciences vol. 396 (2017) pp. 97–113
- X. Chai, Z. Gan, Y. Chen, Y. Zhang, “A visually secure image encryption scheme based on compressive sensing” , Signal Process, vol. 134 (2017) pp. 35-51
- Y. Zhang , L.Y. Zhang , “Exploiting random convolution and random subsampling for image encryption and compression”, Electron. Lett. vol. 51 no. 20 (2015) pp. 1572–1574
- H. Zhu , C. Zhao , X. Zhang , “A novel image encryption–compression scheme using hyper-chaos and Chinese remainder theorem”, Signal Process. Image Commun. vol. 28 no. 6 (2013) pp. 670–680
- Z. Hua, Y. Zhou, “Design of image cipher using block-based scrambling and image filtering”, Information Science vol. 396 no.7 (2017) pp. 97-113
- 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 no. 8 (2013) pp. 4070-4075
- G. Ye, “Image scrambling encryption algorithm of pixel bit based on chaos map”, Pattern Recognition Letters, vol. 31, no. 5 (2010) pp. 347–354
- http://homepages.inf.ed.ac.uk/rbf/HIPR2/fourier.htm, (18 April 2017)
- 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 no. 11 (2016) pp. 248-254
- P. Sharma, D. Mishra, V.K. Sarthi, P. Bhatpahri, R. Shrivastava, “Visual Encryption Using Bit Shift Technique”, International Journal of Scientific Research in Computer Science & Engineering, vol. 5 no. 3 (2017) pp. 57-61
- 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, no.7, (2014) pp. 1- 21
- 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 no. 3 (2015) pp. 1-5
- 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 no.4 (2013) pp.1-6.
- C. Li, K. T. Lo, “Optimal quantitative cryptanalysis of permutation-only multimedia ciphers against plaintext attacks”, Signal Processing, Vol. 91 no. 4 (2011) pp. 949–954.
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