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Nonlinearity measures of random Boolean functions

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Abstract

The r-th order nonlinearity of a Boolean function is the minimum number of elements that have to be changed in its truth table to arrive at a Boolean function of degree at most r. It is shown that the (suitably normalised) r-th order nonlinearity of a random Boolean function converges strongly for all r ≥ 1. This extends results by Rodier for r = 1 and by Dib for r = 2. The methods in the present paper are mostly of elementary combinatorial nature and also lead to simpler proofs in the cases that r = 1 or 2.

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References

  1. Carlet, C.: The complexity of Boolean functions from cryptographic viewpoint, Complexity of Boolean Functions (Dagstuhl, Germany), Dagstuhl Seminar Proceedings, no. 06111 (2006)

  2. Carlet, C.: Boolean functions for cryptography and error-correcting codes. In: Crama, Y., Hammer, P.L. (eds.) Boolean Models and Methods in Mathematics, Computer Science, and Engineering, pp 257–397. Cambridge University Press, Cambridge (2010)

    Chapter  Google Scholar 

  3. Dib, S: Distribution of Boolean functions according to the second-order nonlinearity. In: Arithmetic of finite fields, Lecture Notes in Comput. Sci., vol. 6087, pp 86–96. Springer, Berlin (2010)

    Google Scholar 

  4. Feller, W.: An introduction to probability theory and its applications, Third edition, vol. I. Wiley, New York (1968)

    MATH  Google Scholar 

  5. Halász, G: On a result of Salem and Zygmund concerning random polynomials. Stud. Sci. Math. Hung. 8, 369–377 (1973)

    MathSciNet  MATH  Google Scholar 

  6. Kaufman, T., Lovett, S., Porat, E.: Weight distribution and list-decoding size of Reed-Muller codes. IEEE Trans. Inf. Theory 58(5), 2689–2696 (2012)

    Article  MathSciNet  Google Scholar 

  7. Knudsen, L.R., Robshaw, M.J.B.: Non-linear approximations in linear cryptanalysis. In: Proceedings Eurocrypt’96, Lecture Notes Comput. Sci., vol. 1070, pp 224–236 (1996)

  8. Litsyn, S., Shpunt, A.: On the distribution of Boolean function nonlinearity. SIAM J. Discrete Math. 23(1), 79–95 (2008/09)

    Article  MathSciNet  MATH  Google Scholar 

  9. MacWilliams, F.J., Sloane, N.J.A.: The theory of error-correcting codes. Amsterdam, The Netherlands (1977)

    MATH  Google Scholar 

  10. McDiarmid, C: On the method of bounded differences. In: Siemons, J. (ed.) Surveys in Combinatorics, London Math. Soc. Lectures Notes Ser. 141, pp 148–188. Cambridge University Press, Cambridge (1989)

    Google Scholar 

  11. Olejár, D., Stanek, M.: On cryptographic properties of random Boolean functions. J.UCS 4(8), 705–717 (1998). (electronic)

    MathSciNet  MATH  Google Scholar 

  12. Rodier, F.: Sur la non-linéarité des fonctions booléennes. Acta Arith 115(1), 1–22 (2004)

    Article  MathSciNet  Google Scholar 

  13. Rodier, F.: Asymptotic nonlinearity of Boolean functions. Des. Codes Cryptogr. 40(1), 59–70 (2006)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgments

I thank Claude Carlet for some careful comments on a draft of this paper.

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Correspondence to Kai-Uwe Schmidt.

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Schmidt, KU. Nonlinearity measures of random Boolean functions. Cryptogr. Commun. 8, 637–645 (2016). https://doi.org/10.1007/s12095-015-0164-3

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