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Heuristic Methods for the Design of Cryptographic Boolean Functions

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Heuristic Methods for the Design of Cryptographic Boolean Functions I. Moskovchenko, A. Kuznetsov, S. Kavun et al. / International Journal of Computing, 18(3) 2019, 265-277 Print ISSN 1727-6209 [email protected] On-line ISSN 2312-5381 www.computingonline.net International Journal of Computing HEURISTIC METHODS FOR THE DESIGN OF CRYPTOGRAPHIC BOOLEAN FUNCTIONS Illarion Moskovchenko 1,2), Alexandr Kuznetsov 2,3), Sergii Kavun 4), Berik Akhmetov 5), Ivan Bilozertsev 2,3), Serhii Smirnov 6) 1) Ivan Kozhedub Kharkiv National Air Force University, Sumska str., 77/79, Kharkiv, 61023, Ukraine 2) V. N. Karazin Kharkiv National University, Svobody sq., 6, Kharkiv, 61022, Ukraine, [email protected], [email protected], [email protected] 3) JSC “Institute of Information Technologies”, Bakulin St., 12, Kharkiv, 61166, Ukraine 4) Kharkiv University of Technology “STEP”, Malom’yasnitska st. 9/11, 61010, Kharkiv, Ukraine, [email protected] 5) Yessenov University, 32 microdistricts, 130003, Aktau, The Republic of Kazakhstan, [email protected] 6) Central Ukrainian National Technical University, University Avenue 8, Kropyvnytskyi, 25006, Ukraine, [email protected] Paper history: Abstract: In this article, heuristic methods of hill climbing for cryptographic Received 20 November 2018 Boolean functions satisfying the required properties of balance, nonlinearity, Received in revised form 28 June 2019 Accepted 10 September 2019 autocorrelation, and other stability indicators are considered. A technique for Available online 30 September 2019 estimating the computational efficiency of gradient search methods, based on the construction of selective (empirical) distribution functions characterizing the probability of the formation of Boolean functions with indices of stability not lower than required, is proposed. As an indicator of computational efficiency, an average number of attempts is proposed to be performed using a heuristic Keywords: method to form a cryptographic Boolean function with the required properties. heuristic methods; Comparative assessments of the effectiveness of the heuristic methods are cryptographic Boolean functions; symmetric cryptography; considered. The results of investigations of the cryptographic properties of the nonlinear substitute blocks. formed Boolean functions in comparison with the best known assessments are given. On the basis of the conducted research, it can be concluded that the functions constructed in accordance with the developed method have high persistence indexes and exceed the known functions by these indicators. Copyright © Research Institute for Intelligent Computer Systems, 2019. All rights reserved. 1. INTRODUCTION investigated. In [12, 13], the influence of S-blocks on avalanche effects, differential and linear An important element of most modern symmetric properties of block ciphers is investigated. The ciphers are non-linear replacement blocks [1-7], papers [14, 15] are dedicated to the study of the which are described with the help of Boolean or, in properties of nonlinear replacement nodes in modern general, vector cryptographic functions [6]. stream ciphers in comparison with the "Strumok" Indicators of the cryptographic strength of such algorithm proposed as a new standard of stream functions (balance, nonlinearity, autocorrelation, encryption in Ukraine [16]. etc.) directly affect the efficiency of symmetric Methods for constructing S-blocks are ciphers, their resistance to most modern investigated by many authors, for example, in [17- cryptanalytical attacks [5-15]. In particular, the 20]. However, the most developed and widespread is algebraic properties of S-blocks of modern block the mathematical apparatus of cryptographic ciphers are investigated in [5-7] and their influence Boolean functions [21-28]. In particular, a new on sustainability to algebraic cryptanalysis is shown. recursive construction of a Boolean function with In [8-11], combinatorial properties of non-linear maximum algebraic immunity is presented in [21]; knots in the context of the security evaluation of in [22, 23] genetic algorithms for constructing various encryption modes and key schedules were Boolean functions with the required cryptographic 265 I. Moskovchenko, A. Kuznetsov, S. Kavun et al. / International Journal of Computing, 18(3) 2019, 265-277 properties are examined; in [24] the method of The sequence of the function f is (1,-1) – a simulation of annealing is investigated; evolutionary f () f () sequence, defined as ( ( 1) 0 , ( 1) 1 , …, methods are studied in [25, 26]; papers [27, 28] are f () dedicated to the heuristic methods of gradient ( 1) 2n1 ) [21-28]. search. The truth table of a function f is (0,1) - a The purpose of this paper is to continue studies n sequence, defined as (f(0), f(1), f () ) [21-28]. of the method of gradient descent, first proposed in 2 1 [28], an assessment of its computational complexity The sequence of the function f is balanced if its in comparison with the closest analog in [27]. For (0,1) -sequence ((1, -1) - sequence) contains the this purpose, the necessary terms and definitions in same number of zeros and ones (ones and minus Section 2 are introduced; the heuristic methods ones). The function f is balanced if its sequence is studied in [27, 28] are summarized in Section 3 and balanced [21-28]. the calculated data for the required number of The balance of the function is an indicator of operations for the realization of gradient descent stability, reflecting the weakness of the output (Table I) is provided. Section 4 evaluates the sequence to statistical attacks. properties of the gradient-lift method for the An affine function f is a function of the form f = formation of high non-linear correlation-immune a1x1 … anxn с, где aj, с GF(2), j = 1, 2,..., cryptographic Boolean functions. In section 5 a п. Function f is called linear, if с = 0 [21-28]. methodology for assessing the effectiveness of The Hamming weight of the vector ((0,1)- heuristic methods is proposed and the results of sequence ), denoted by W(), is the number of comparative studies are represented. In particular, it ones in the vector (sequence) [21-28]. has been shown that the method of gradient descent The Hamming distance d (f,g) between the in [28] for a significantly smaller number of sequences of two functions f and g is the number of iterations (in dozens of times) makes it possible to positions in which the sequences of these functions form cryptographic Boolean functions with the are different [21-28]. required indices of nonlinearity and autocorrelation. The nonlinearity of the NS transformation is the Section 6 presents the results of investigations of the minimum Hamming distance between the output cryptographic properties of the formed Boolean sequence S and all output sequences of affine functions and compares them with the best known functions over a certain field [21-28]: NS = min assessments. In conclusion, the obtained results are {d(S,)}, where - is the set of affine functions. summarized and directions for further research are The nonlinearity of the function Nf is the minimal formulated briefly. Hamming distance Nf between the function f and all affine functions over GF (2n) [21-28]: where is the 2. INDICES OF STABILITY set of affine functions. OF CRYPTOGRAPHIC BOOLEAN For an arbitrary function f, the nonlinearity of Nf n n – 1 n/2 – 1 FUNCTIONS over GF (2 ) can reach [21-28]: Nf 2 – 2 . For a balanced function f over GF (2n) (n 3), the The basic concepts and definitions of the nonlinearity of Nf can reach [21-28]: mathematical apparatus of Boolean algebra used in evaluating the effectiveness of non-linear nodes to n1 n /2 1 replace symmetric ciphers were introduced in [21- 2 2 2 ,n 2 k , N f , 28]. 2n1 2 n /2 1 ,n 2 k 1, The Boolean function f of n variables is the function [21-28], variables is the function that maps n from the field GF(2 ) of all binary vectors x = (x1, where x – is the maximal even integer less …, xn) of length n to the field GF(2). Usually Boolean functions are represented in algebraic than or equal to х. Non-linearity of the function is an indicator normal form (ANF) and are considered as the sum of the products of the component coordinates. reflecting the stability of functions to correlative The algebraic degree deg (f) is the degree of the (linear) attacks. longest summand of a function represented in an The function f has a correlation immunity of algebraic normal form. Algebraic degree reflects the order k if the output sequence of the function y Y resistance to analytical attacks, designed to reduce is statistically independent of any subset of k input this function to cryptographically weak (linear). coordinates [21-28]: {x1, …, xk} P(y Y / {x1, …, xk} Х) = P(y Y). Equivalent definition of correlation immunity in terms of the Walsh transform [21-28]: the function f 266 I. Moskovchenko, A. Kuznetsov, S. Kavun et al. / International Journal of Computing, 18(3) 2019, 265-277 n over the field GF(2 ) has correlation immunity of f(x) f(x α) is balanced α Vn, W(α) 0; order k, CI(k) if its Walsh transform satisfies the f(x) , x takes the value of one 2n-1 2n/2 – 1 equality F() = 0 for all V such as 1 W() n times α V ; k: V , F() = 0, CI (f) = k. n n f(x) h(x), where h(x) – affine function, is also a The Walsh transformation F() of the function f bent function. over the field GF(2n) is defined as the real-valued Autocorrelation function ̂() for s 0...n 1 is function [21-28]: 2 defined as F() = 2-n ( 1) f(), x x , x . where Vn, f(х), ,x N (,x -is the scalar product w1x1 … wnxn) . The value of autocorrelation reflects the stability Correlation-immune function of the k-th order is of the functions to the class of analytic attacks, a function possessing correlation immunity of the designed to find a correlation between the fragments order of k.
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