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Tytuł artykułu

A Digital Image Encryption Algorithm Based on Hyper-chaotic Cellular Neural Network

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Języki publikacji
EN
Abstrakty
EN
Using Chaotic characteristics of dynamic system is a promising direction to design cryptosystems that play a pivotal role in a very important engineering application of cognitive informatics, i.e., information assurance and security. However, encryption algorithms based on the lowdimensional chaotic maps face a potential risk of the keystream being reconstructed via return map technique or neural network method. In this paper, we propose a new digital image encryption algorithm that employs a hyper-chaotic cellular neural network. To substantiate its security characteristics, we conduct the following security analyses of the proposed algorithm: key space analysis, sensitivity analysis, information entropy analysis and correlation coefficients analysis of adjacent pixels. The results demonstrate that the proposed encryption algorithm has desirable security properties and can be deployed as a cornerstone in a sound security cryptosystem. The comparison of the proposed algorithm with five other chaos-based image encryption algorithms indicates that our algorithm has a better security performance.
Wydawca
Rocznik
Strony
269--282
Opis fizyczny
bibliogr. 28 poz., fot., tab., wykr.
Twórcy
autor
autor
autor
  • College of Electronic Information Engineering Chongqing University of Science and Technology, Chongqing 400050, China, pengjun70@126.com
Bibliografia
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  • [3] Matthews, R.: On the derivation of a chaotic encryption algorithm, Cryptologia, XIII(1), 1989, 29-42.
  • [4] Fridrich, J.: Symmetric ciphers based on two-dimensional chaotic maps, Int. J. Bifurcation and Chaos, 8(6), 1998, 1259-1284.
  • [5] Fridrich, J.: Image encryption based on chaotic maps, Proc. IEEE Int. Conf. Systems, Man, and Cybernetics, Orlando, FL, USA, 1997.
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  • [7] Alvarez, G., Li, S. J.: Some basic cryptographic requirements for chaos-based cryptosystems, Int. J. Bifurcation and Chaos, 16(8), 2006, 2129-2151.
  • [8] P´erez, G., Cerdeira, H. A.: Extracting messages masked by chaos, Phys. Rev. Lett., 74(11), 1995, 1970-1973.
  • [9] Yang, T., Lin, B. Y., Chun, M. Y.: Application of neural networks to unmasking chaotic secure communication, Physica D, 124(1-3), 1998, 248-257.
  • [10] Parker, A. T., Short, K. M.: Reconstructing the keystream from a chaotic encryption scheme, IEEE Trans. Circuits Syst. I, 48(5), 2001, 624-630.
  • [11] Yen, J. C., Guo, J. I.: A new chaotic key-based design for image encryption and decryption, Proc. IEEE Int. Conf. Circuits and Systems, Geneva, Switzerland, 2000.
  • [12] Li, S. J., Zheng, X.: Cryptanalysis of a chaotic image encryptionmethod, Proc. IEEE Int. Symposium Circuits and Systems, Phoenix, AZ, USA, 2002.
  • [13] Chen, G., Mao, Y., Chui, C. K.: A symmetric image encryption based on 3D chaotic maps, Chaos, Solitons & Fractals, 21(3), 2004, 749-761.
  • [14] Gao, T. G., Chen, Z. Q.: A new image encryption algorithm based on hyper-chaos, Phys. Lett. A, 372(4), 2008, 394-400.
  • [15] Mascolo, S., Grassi, G.: Observers for hyperchaos synchronization with application to secure communications, Proc. IEEE Int. Conf. on Control Applications, Trieste, Italy, 1998.
  • [16] He, Z., Li, K.: TDMA secure communication based on synchronization of Chua's circuits, J. Circuit Syst. Comp., 10(3-4), 2000, 147-158.
  • [17] Udaltsov, V. S., Goedgebuer, J. P., Larger, L., Rhodes, W. T.: Communicating with optical hyperchaos: information encryption and decryption in delayed nonlinear feedback systems, Phys. Rev. Lett., 86(9), 2001, 1892-1895.
  • [18] Goedgebuer, J. P., Levy, P., Larger, L., Chen,C. C., Rhodes,W. T.: Optical communication with synchronized hyperchaos generated electrooptically, IEEE Journal of Quantum Electronics, 38(9), 2002, 1178-1183.
  • [19] Chua, L. O., Yang, T.: Cellular neural network theory, IEEE Trans. Circuits System, 35(10), 1988, 1257-1272.
  • [20] Csapodi, M., Vandewalle, J., Roska, T.: High speed calculation of cryptographic hash functions by CNN chips, Fifth IEEE International Workshop on Cellular Neural Networks and their Applications, London, England, 1998.
  • [21] Gao, Q., Moschytz, G. S.: Fingerprint feature matching using CNNs, Proceedings of the 2004 International Symposium on Circuits and Systems, Vancouver, Canada, 2004.
  • [22] Yang, Z. X., Karahoca, A.: An anomaly intrusion detection approach using cellular neural networks, Computer and Information Sciences - ISCIS'06 (A. Levi, H. Yenigun, E. Savas, et al., Eds.), LNCS 4263, Springer-Berlin, 2006.
  • [23] He, Z. Y., Zhang, Y. F., Lu, H. T.: The dynamic character of cellular neural network with application to secure communication, Journal of China Institute of Communications, 20(3), 1999, 59-67.
  • [24] Shannon, C. E.: Communication theory of secrecy system, The Bell System Technical Journal, 28(4), 1949, 656-715.
  • [25] Behnia, S., Akhshani, A., Mahmodi, H., Akhavan, A.: A novel algorithm for image encryption based on mixture of chaotic map, Chaos, Solitons & Fractals, 35(2), 2008, 408-419.
  • [26] Gao, H. J., Zhang, Y. S., Liang, S. Y., Li, D. Q.: A new chaotic algorithm for image encryption, Chaos, Solitons & Fractals, 29(2), 2006, 393-399.
  • [27] Rhouma, R., Meherzi, S., Belghith, S.: OCML-based colour image encryption, Chaos, Solitons & Fractals, 2008, in press, doi:10.1016/j.chaos.2007.07.083.
  • [28] Zhang, W., Peng, J., Yang, H. Q., Wei, P. C.:A digital image encryption scheme based on the hybrid of cellular neural network and logistic map, Advances in Neural Networks - ISNN'05 (J. Wang, X. Liao, Z. Yi Eds.), LNCS 3497, Springer-Berlin, 2005.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS8-0004-0018
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