A combined DCA: GA for constructing highly nonlinear balanced boolean functions in cryptography

  • Authors:
  • Hoai Minh Le;Hoai An Le Thi;Tao Pham Dinh;Pascal Bouvry

  • Affiliations:
  • Laboratory of Theoretical and Applied Computer Science (LITA EA 3097) UFR MIM, University of Paul Verlaine - Metz, Metz, France 57045;Laboratory of Theoretical and Applied Computer Science (LITA EA 3097) UFR MIM, University of Paul Verlaine - Metz, Metz, France 57045;Laboratory of Modelling, Optimization and Operations Research, National Institute for Applied Sciences - Rouen, Mont Saint Aignan Cedex, France 76131;Computer Science Research Unit, University of Luxembourg, Luxembourg, Luxembourg 1359

  • Venue:
  • Journal of Global Optimization
  • Year:
  • 2010

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Abstract

Substitution boxes, aka S-boxes, are a key component of modern crypto-systems. Several studies and developments were carried out on the problem of building high-quality S-boxes in the last few years. Qualities of such boxes, such as nonlinearity and balance, steer the robustness of modern block ciphers. This work is concerned with the construction of highly nonlinear balanced Boolean functions. A deterministic optimization model which is the minimization of a polyhedral convex function on a convex polytope with 0---1 variables is introduced. A local deterministic optimization approach called DCA (Difference of Convex functions Algorithm) is investigated. For finding a good starting point of DCA we propose two versions of a combined DCA---GA (Genetic Algorithm) method. Numerical simulations prove that DCA is a promising approach for this problem. Moreover the combination of DCA---GA improves the efficiency of DCA and outperforms other standard approaches.