A self-adapting image encryption algorithm based on spatiotemporal chaos and ergodic matrix

doi:10.1088/1674-1056/22/8/080503

Abstract To ensure the security of a digital image, a new self-adapting encryption algorithm based on the spatiotemporal chaos and ergodic matrix is proposed in this paper. First, the plain-image is divided into different blocks of the same size, and each block is sorted in ascending order to obtain the corresponding standard ergodic matrix. Then each block is encrypted by the spatiotemporal chaotic system and shuffled according to the standard ergodic matrix. Finally, all modules are rearranged to acquire the final encrypted image. In particular, the plain-image information is used in the initial conditions of the spatiotemporal chaos and the ergodic matrices, so different plain-images will be encrypted to obtain different cipher-images. Theoretical analysis and simulation results indicate that the performance and security of the proposed encryption scheme can encrypt the image effectively and resist various typical attacks.

Keywords: spatiotemporal chaos ergodic matrix standard map image encryption

Received: 20 November 2012
Revised: 15 January 2013
Accepted manuscript online:

PACS:	05.45.-a	(Nonlinear dynamics and chaos)
	05.45.Gg	(Control of chaos, applications of chaos)
	05.45.Ra	(Coupled map lattices)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. U0735004 and 60972133), the Natural Science Foundation of Guangdong Province, China (Grant No. 05006593), the Project Team for Natural Science Foundation of Guangdong Province, China (Grant No. 9351064101000003), Energy Technology Key Laboratory Project of Guangdong Province, China (Grant No. 2008A060301002), and the Fundamental Research Funds for the Central Universities, China (Grant No. X2dXD2116370).

Corresponding Authors: Luo Yu-Ling
E-mail: luo.yuling@mail.scut.edu.cn

Cite this article:

Luo Yu-Ling (罗玉玲), Du Ming-Hui (杜明辉) A self-adapting image encryption algorithm based on spatiotemporal chaos and ergodic matrix 2013 Chin. Phys. B 22 080503

[1]	Shannon C E 1949 Bell System Technology Journal 28 656
[2]	Schneier B 1995 Cryptography: Theory and Practice (Boca Raton (FL): CRC Press)
[3]	Brown R and Chua L O 1996 Int. J. Bifur. Chaos 6 219
[4]	Fridrich J 1998 Int. J. Bifur. Chaos 8 1259
[5]	Chen G R, Mao Y B and Chui C K 2004 Chaos, Solitons and Fractals 21 749
[6]	Pareek N K, Patidar V and Sud K K 2006 Image and Vision Computing 24 926
[7]	Pareek N K, Patidar V and Sud K K 2005 Commun. Ninlinear Sci. Numer. Simul. 10 715
[8]	Li C Q, Li S J, Asim M, Nunez J, Alvarez G and Chen G R 2009 Image and Vision Computing 27 1371
[9]	Li C Q, Li S J, Alvarez G, Chen G R and Lo Kwok-Tung 2008 Chaos, Solitons and Fractals 37 299
[10]	Patidar V, Pareek N K and Sud K K 2010 Commun. Nonlinear Sci. Numer. Simul. 14 2755
[11]	Patidar V, Pareek N K and Sud K K 2009 Commun. Nonlinear Sci. Numer. Simul. 14 3056
[12]	Rhouma R, Solak E and Belghith S 2010 Commun. Nonlinear Sci. Numer. Simul. 15 1887
[13]	Li C Q, Li S J and Lo K T 2011 Commun. Nonlinear Sci. Numer. Simulat. 16 837
[14]	Akhavan A, Samsudin A and Akhshani A 2011 Journal of the Franklin Institute 348 1797
[15]	Sathishkumar G A and Bhoopathy Bagan K 2011 Wseas Transactions on Computers 10 169
[16]	Ye R S 2011 Opt. Commun. 284 5290
[17]	Zhu Z L, Zhang W, Wong K W and Yu H 2011 Inf. Sci. 181 1171
[18]	Fu C, Lin B B, Miao Y S, Liu X and Chen J J 2011 Opt. Commun. 284 5415
[19]	Li C Q and Lo K T 2011 Signal Processing 91 949
[20]	Wang Y, Wong K W, Liao X F and Chen G R 2011 Appl. Soft Comput. 11 514
[21]	Ye G D 2011 The Imaging Science Journal 59 183
[22]	Wang X Y and Jin C Q 2012 Opt. Commun. 285 412
[23]	Wang X Y and Teng L 2012 Chin. Phys. B 21 020504
[24]	Sun F Y, Lü Z W and Liu S T 2010 Opt. Commun. 283 2066
[25]	Sun F Y and Lü Z W 2011 Chin. Phys. B 20 040506
[26]	Wang X Y and Teng L 2011 Nonlinear Dynamics 67 365
[27]	Wang X Y, Zhang N, Ren X L and Zhang Y L 2011 Chin. Phys. B 20 020507
[28]	Banerjee S, Rondoni L, Mukhopadhyay S and Misra A P 2011 Opt. Commun. 284 2278
[29]	Yuen C H and Wong K W 2012 Chin. Phys. B 21 010502
[30]	Wang Z, Huang X, Li N and Song X N 2012 Chin. Phys. B 21 050506
[31]	Kaneko K 1985 Prog. Theor. Phys. 74 1033
[32]	Cheng G, Zhao X Y and Li J L 2005 Journal of Software 16 1975

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A self-adapting image encryption algorithm based on spatiotemporal chaos and ergodic matrix

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