A Novel Construction of Dynamic S-Box With High Nonlinearity Using Heuristic Evolution

Abstract

The security and privacy of data have been one of the major challenges for service providers dealing with public data since decades. To cope with these challenges, most of the organizations rely on the adoption of cryptographic methods for protecting data against any illegitimate efforts and attacks. Modern day cryptographic ciphers utilized one or more substitution-boxes (S-boxes) which facilitate to achieve strong security of plain data during encryption and legal decoding of it during decryption process. Security of ciphers is directly proportional to the cryptographic strength of S-boxes. This paper proposes to suggest an efficient, novel and simple method based on some modular operations for the construction of dynamic Sboxes with high nonlinear nature using heuristic evolution strategy. A large number of strong S-boxes can straightforwardly be erected by making slight variations in the parameters of the anticipated method. A specimen S-box is constructed and its critical performance analysis against standard security criteria including nonlinearity, strict avalanche criterion, bit independence criterion, differential uniformity, linear probability, and fixed points have been done to justify high cryptographic strength. The generated S-box is also applied to encrypt digital images to assess its cryptographic application performance. The performance and comparison study validates that the proposed S-box has better performance strength and true candidature for cryptographic application in the area of image security.

Stochastic Fractal Search Algorithm Improved with Opposition-Based Learning for Solving the Substitution Box Design Problem

“…This work proposed the cryptanalysis of an image encryption scheme, in which the formation of the substitution boxes was performed using a combination of chaotic maps, involving Lorenz [26] and Rossler [27]. The proposal in [28] utilized a heuristic evolution strategy based on affine transformation and permutation process. The experiments were evaluated according to standard criteria, fixed point analysis, and computational time.…”

Construction of Optimized Dynamic S-Boxes Based on a Cubic Modular Transform and the Sine Function

“…It is visually evident that nonlinearity scores of initial S-boxes get improvised up to a remarkable extent which justifies the consistency of the complete proposed S-box construction scheme. [62,63,72,73,75,76] which have applied some heuristic approaches. Table 11 demonstrates that the computational time of generating our proposed S-box is handsomely inspirational as compared to those of [62,63,72,73,75,76] while NL scores of these approaches are nearly equal and quite high.…”

“…[62,63,72,73,75,76] which have applied some heuristic approaches. Table 11 demonstrates that the computational time of generating our proposed S-box is handsomely inspirational as compared to those of [62,63,72,73,75,76] while NL scores of these approaches are nearly equal and quite high. Although several researchers projected novel techniques to generate S-boxes with nonlinearity scores ~ 112, such techniques are deficient of one or more security standards like presence of fixed points [30,70,71,72,73], nonbijectiveness [74], static heuristic approach [75], high DU value and complicated generation procedure [76], application of static irreducible polynomial [72,75], etc.…”

New Genetic Operators for Developing S-Boxes With Low Boomerang Uniformity

“…Reinforcement learning was used to train a method expressed in the Markov decision process to an agent to generate S-boxes that can effectively resist the side-channel attack [15]. Heuristic evolution strategy improved the initial S-Boxes created by a modular operation [16]. The S-box construction time was reduced by constrainedly maximizing the nonlinearity of the S-boxes created by a random-restart hill-climbing algorithm [17].…”