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New digital images cryptography algorithm using butterflies and Banyan networkconnected

Journal Name:

  • Cumhuriyet Üniversitesi Fen Fakültesi Fen Bilimleri Dergisi

Publication Year:

  • 2015

Key Words:

Author NameUniversity of Author
Abstract (2. Language): 
Information security is a critical issue for data privacy of peoples and organizations. A powerful tool to satisfy this requirement is cryptography. Cryptography is a method of securing which is done by using a reversible mathematical relationship. As images are widely used in digital products and because of its special nature, has its special cryptographic algorithms. In this paper, a new cryptography algorithm for digital images are proposed by using the butterfly and Banyan network connectivity which are one of the tools of parallel processors; In this algorithm, the image are divided into the some blocks and fragmented by using the technique of displacement and a butterfly network is pixels in each block and then some changes are applied to the bits of each pixel. To evaluate different algorithms, we have used some visual test, correlation analysis and histogram analysis error criteria. Experimental results show that the proposed method, besides having good visual quality, error criteria reduced NPCR, MA E and UACI, respectively, at 13.5237, 13.2083 and 0.935. Also proposed algorithm is able to reduce the correlation of pixels in the horizontal, vertical and diagonal average at 0043/0, 0026/0 and 0039/0.
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REFERENCES

References: 

Che. S, Che. Z & Ma.B. (2008). An Improved Image Scrambling Algorithm. Second International Conference On Genetic And Evolutionary Computing, Pp.495-499.
Ding.W, Yan.W& Qi. D. (2000). Digital Image Scrambling. Progress In Natural Science, Vol. 11, Pp.7-14.
Feng-Ying. H & Cong-Xu .Z.(2011). An Novel Chaotic Image Encryption Algorithm Based On Tangent-Delay Ellipse Reflecting Cavity Map System. Procedia Engineering, Vol. 23, Pp. 186-191.
Gu. G.S. & Han. G.Q. (2006). The Application Of Chaos And DWT In Image Scrambling. IEEE Conference on Industrial Electronics And Applications, Pp. 3729 – 3733.
Hyndman.R. J. & Koehler. A. B. (2006). Another Look At Measures Of Forecast Accuracy, International Journal Of Forecasting.
Jiancheng. Z, Ward. R.K. & Dongxu.Q. (2004). A New Digital Image Scrambling Method Based On Fibonacci Numbers, In Proceedings Of The International Symposium On Circuits And Systems,Vol 3.
Jolfaei. A & Mirghadri .A. (2010). Survey: Image Encryption Using Salsa20. International Journal of Computer Science Issues, Vol. 5, Pp. 213-220.
Kanso. A & Ghebleh. M. (2012). A Novel Image Encryption Algorithm Based On A 3D Chaotic Map. Nonlinear Science and Numerical Simulation, Vol .17, Pp. 2943-2959.
Pareek. N.K, Vinod .P & Sud.K.K. (2006). Image Encryption Using Chaotic Logistic Map. The Journal Of Image And Vision Computing, Vol .24, Pp. 926-934.
Rakesh. S, Ajitkumar. A .Kaller, Shadakshari. B. C &Annappa .B. (2012). Image Encryption Using Block Based Uniform Scrambling And Chaotic Logistic Mapping. International Journal on Cryptography and Information Security, Vol .2, Pp. 49-57.
Wei. D, Wei-Qi. Y& Dong-Xu. Q. (1999). Digital Image Scrambling Technology Based On Gray Code. International Conference on Computer Aided Design & Computer Graphics, Vol. 3. Pp.900-904.
Wei. D. (2001). Digital Image Scrambling, Progress In Natural Science Journal, Vol 11, P. 454-460.
Willmott. C.J & Matsuura.K. (2005). Advantages Of The Mean Absolute Error (MAE) Over The Root Mean Square Error (RMSE) In Assessing Average Model Performance. Climate Research Clime Res, Vol .30, Pp.79-82.
Wong. K.W & Kwok. B.S.H. (2009). An Efficient Diffusion Approach For Chaos-Based Image Encryption .Chaos Solitons & Fractals, Vol.41, Pp. 2652-2663.
Wu. Y, Noonan. J.P & Agaian. S. (2011). Shannon Entropy Based Randomness Measurement and Test For Image Encryption. Journal of Information Sciences.Pp.1-23.
Xiangdong. L, Junxing. Z, Jinhai. Z & Xiqin. H. (2008).Image Scrambling Algorithm Based on Chaos Theory and Sorting Transformation, International Journal of Computer Science and Network Security, Vol 8, P. 64-68.
Firouzabadi and Latif
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Ye. G. (2010). Image Scrambling Encryption Algorithm Of Pixel Bit Based On Chaos Map. Pattern Recognition Letters, Vol .31, Pp.354-347.
Ye. R & Zhao. H. (2012). An Efficient Chaos Based Image Encryption Scheme Using Affine Modular Maps. International Journal of Computer Network and Information Security, Vol .4, Pp.41-45.
Ying. W, Zhao .Z & Lelin. Z. (2007). A Fault-Tolerable Encryption Algorithm for Two-Dimensional Digital Image, IEEE Conference on Industrial Electronics and Applications, P.2737 - 2741.

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