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International Conference on Engineering Applications of Neural Networks

EANN 2017: Engineering Applications of Neural Networks pp 49–60Cite as

Memristor Based Chaotic Neural Network with Application in Nonlinear Cryptosystem

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 744))

Abstract

The global shift towards digitization has resulted in intensive research on Cryptographic techniques. Chaotic neural networks, augment the process of cryptography by providing increased security. In this paper, a description of an algorithm for the generation of an initial value for encryption using neural network involving memristor and chaotic polynomials is provided. The chaotic series that is obtained is combined with nonlinear 1 Dimensional and 2 Dimensional chaotic equations for the encryption process. A detailed analysis is performed to find the fastest converging neural network, complemented by the chaotic equations to produce least correlated ciphertext and plaintext. The use of Memristor in Neural Network as a generator for chaotic initial value as the encryption key and the involvement of nonlinear equations for encryption, makes the communication more confidential. The network can further be used for secure multi receiver systems.

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References

  1. Wang, L., Duan, M., Duan, S.: Memristive chebyshev neural network and its applications in function approximation. Mathe. Probl. Eng. 2013 (2013). Article ID 429402. doi:10.1155/2013/429402

  2. Chua, L.: Memristor-the missing circuit element. IEEE Trans. Circuit Theory 18(5), 507–519 (1971)

    Article  Google Scholar 

  3. Prodromakis, T., Toumazou, C.: A review on memristive devices and applications. In: 2010 17th IEEE International Conference on Electronics, Circuits, and Systems (ICECS). IEEE (2010)

    Google Scholar 

  4. Pershin, Y.V., Di Ventra, M.: Experimental demonstration of associative memory with memristive neural networks. Neural Netw. 23(7), 881–886 (2010)

    Article  Google Scholar 

  5. Matthews, R.: On the derivation of a encryption algorithm. Cryptologia 13(1), 29–42 (1989)

    Article  MathSciNet  Google Scholar 

  6. Pecora, L.M., Carroll, T.L.: Synchronization in chaotic systems. Phys. Rev. Lett. 64(8), 821 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  7. Zhen, P., et al.: A survey of chaos-based cryptography. In: 2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC). IEEE (2014)

    Google Scholar 

  8. Kim, K.-K.K., et al.: Wiener’s polynomial chaos for the analysis and control of nonlinear dynamical systems with probabilistic uncertainties [historical perspectives]. IEEE Control Syst. 33(5), 58–67 (2013)

    Article  MathSciNet  Google Scholar 

  9. Wahab, H.B.A., Jaber, T.A.: Improve NTRU algorithm based on Chebyshev polynomial. In: 2015 World Congress on Information Technology and Computer Applications Congress (WCITCA). IEEE (2015)

    Google Scholar 

  10. Nyberg, K.: Generalized feistel networks. In: Kim, K., Matsumoto, T. (eds.) ASIACRYPT 1996. LNCS, vol. 1163, pp. 91–104. Springer, Heidelberg (1996). doi:10.1007/BFb0034838

    Chapter  Google Scholar 

  11. Pareek, N.K., Patidar, V., Sud, K.K.: Cryptography using multiple one-dimensional chaotic maps. Commun. Nonlinear Sci. Numer. Simul. 10(7), 715–723 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  12. Fridrich, J.: Symmetric ciphers based on two-dimensional chaotic maps. Int. J. Bifurcat. Chaos 8(06), 1259–1284 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  13. Shi, X., et al.: A novel memristive electronic synapse-based Hermite chaotic neural network with application in cryptography. Neurocomputing 166, 487–495 (2015)

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank the faculty and staff of the Department of Electronics and Communication Engineering, SRM University for their support and guidance.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, SRM University, SRM Nagar, Kattankulathur, Chennai, India

    N. Varsha Prasad, Sriharini Tumu & A. Ruhan Bevi

Authors
  1. N. Varsha Prasad
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  2. Sriharini Tumu
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  3. A. Ruhan Bevi
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Corresponding author

Correspondence to N. Varsha Prasad .

Editor information

Editors and Affiliations

  1. Politecnico di Milano, Milan, Italy

    Giacomo Boracchi

  2. Democritus University of Thrace, University Campus, Xanthi, Greece

    Lazaros Iliadis

  3. School of Computing Science and Digital Media, Robert Gordon University, Aberdeen, United Kingdom

    Chrisina Jayne

  4. Univesity of Ioannina, Ioannina, Greece

    Aristidis Likas

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Prasad, N.V., Tumu, S., Bevi, A.R. (2017). Memristor Based Chaotic Neural Network with Application in Nonlinear Cryptosystem. In: Boracchi, G., Iliadis, L., Jayne, C., Likas, A. (eds) Engineering Applications of Neural Networks. EANN 2017. Communications in Computer and Information Science, vol 744. Springer, Cham. https://doi.org/10.1007/978-3-319-65172-9_5

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  • DOI: https://doi.org/10.1007/978-3-319-65172-9_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65171-2

  • Online ISBN: 978-3-319-65172-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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