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On Application of Neural Networks for S-Boxes Design

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Advances in Web Intelligence (AWIC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3528))

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Abstract

In the paper a new schedule of S-boxes design is considered. We start from motivation from block cipher practice. Then, the most popular S-box design criteria are presented, especially a possibility of application of Boolean bent-functions. Finally, we propose integrating neural networks (playing a role of Boolean functions with appropriate properties) in the design process.

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References

  1. FIPS 46-3, Data Encryption Standard (DES), NIST (1999)

    Google Scholar 

  2. Kotulski, Z.: Construction of block ciphers: new possibilities (Polish). Mat. Stosow. 4(45), 1–24 (2003)

    MathSciNet  Google Scholar 

  3. FIPS 197, Advanced Encryption Standard (AES). In: NIST 2001(2001)

    Google Scholar 

  4. GOST 28147-89, Cryptographic Protection for Data Processing Systems. Cryptographic Transformation Algorithm, Government Standard of the U.S.S.R. (1990)

    Google Scholar 

  5. Gan, L., Simmons, S., Tavares, S.: A new family of stream ciphers based on cascades small S-boxes. IEEE, Los Alamitos (1997)

    Google Scholar 

  6. Matsui, M.: Linear Cryptanalysis Method for DES Cipher. In: Helleseth, T. (ed.) EUROCRYPT 1993. LNCS, vol. 765, pp. 386–397. Springer, Heidelberg (1994)

    Google Scholar 

  7. Biham, E., Shamir, A.: Differential Cryptanalysis of Data Encryption Standard. Springer, Berlin (1993)

    MATH  Google Scholar 

  8. Adams, C.M., Tavares, S.E.: Designing S-boxes for Ciphers Resistant to Differential Cryptanalysis

    Google Scholar 

  9. Horzyk, A., Tadeusiewicz, R.: Self-Optimizing Neural Networks. In: Yin, F.-L., Wang, J., Guo, C. (eds.) ISNN 2004. LNCS, vol. 3173, pp. 150–155. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  10. Knudsen, L.R.: Practically Secure Feistel Ciphers. In: Anderson, R. (ed.) FSE 1993. LNCS, vol. 809, pp. 211–222. Springer, Heidelberg (1994)

    Google Scholar 

  11. Webster, A.F., Tavares, S.E.: On the design of S-boxes. In: Williams, H.C. (ed.) CRYPTO 1985. LNCS, vol. 218, pp. 523–534. Springer, Heidelberg (1986)

    Google Scholar 

  12. Mister, S., Adams, C.: Practical S-Box Design. In: Workshop on Selected Areas in Cryptography (SAC 1996) Workshop Record, pp. 61–76. Queens University (1996)

    Google Scholar 

  13. Adams, C.M., Tavares, S.E.: The Use of Bent Sequences do Achieve Higher Order Strict Criterion in S-Box Design TRTR 90-013 (January 1990)

    Google Scholar 

  14. Grocholewska-Czurylo, A.: Avalanche and propagation properties of random bent Boolean functions. In: Proc. RMCIS 2003, p. 9.3. Zegrze (2003)

    Google Scholar 

  15. Szmidt, J.: Cryptographic properties of the Boolean functions. In: Proceedings of the 5th National Conference on Cryptography ENIGMA 2001, Warsaw (2001)

    Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Kotlarz, P., Kotulski, Z. (2005). On Application of Neural Networks for S-Boxes Design. In: Szczepaniak, P.S., Kacprzyk, J., Niewiadomski, A. (eds) Advances in Web Intelligence. AWIC 2005. Lecture Notes in Computer Science(), vol 3528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11495772_38

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  • DOI: https://doi.org/10.1007/11495772_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26219-0

  • Online ISBN: 978-3-540-31900-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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