APN Permutations

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Characterization of Permutations

Component Functions

An [math]\displaystyle{ (n,n) }[/math]-function [math]\displaystyle{ F }[/math] is a permutation if and only if all of its components [math]\displaystyle{ f_λ }[/math] for [math]\displaystyle{ \lambda\in\mathbb{F}^*_{2^n} }[/math] are balanced.

Autocorrelation Functions of the Directional Derivatives

For any boolean function [math]\displaystyle{ f }[/math], we denote by [math]\displaystyle{ \mathcal{F}(f) }[/math] the following value related to the Fourier (or Walsh) transform of [math]\displaystyle{ f }[/math]:

[math]\displaystyle{ \mathcal{F}(f)=\sum_{x\in\mathbb{F}_{2^n}}(-1)^{f(x)}=2^n-2wt(f). }[/math]

The characterization in terms of the component functions given above can be equivalently expressed as

[math]\displaystyle{ \sum_{a \in \mathbb{F}_{2^n}^*} \mathcal{F}(D_af_\lambda) = -2^n }[/math]

for any [math]\displaystyle{ λ\in\mathbb{F}^*_{2^n} }[/math].

Equivalently [1], [math]\displaystyle{ F }[/math] is a permutation if and only if

[math]\displaystyle{ \sum_{\lambda \in \mathbb{F}_{2^n}^*} \mathcal{F}(D_af_\lambda) = -2^n }[/math]

for any [math]\displaystyle{ a\in\mathbb{F}^*_{2^n} }[/math].

Characterization of APN Permutations

Up to CCZ-equivalence, all of the APN permutations known so far belong to a few families, namely:[2]

1. APN monomial functions in odd dimension.

2. One infinite family of quadratic polynomials in dimension [math]\displaystyle{ 3n }[/math], with [math]\displaystyle{ n }[/math] odd and [math]\displaystyle{ gcd(n,3)=1 }[/math].[3]

3. Dillon's permutation in dimension 6.[4]

4. Two sporadic quadratic APN permutations in dimension 9.[5]

On the component functions

Clearly we have that no component function can be of degree 1. (This result is true for general APN maps)

For [math]\displaystyle{ n }[/math] even we have also that no component can be partially-bent[6]. This implies that, in even dimension, no component can be of degree 2.

Autocorrelation Functions of the Directional Derivatives

An [math]\displaystyle{ (n,n) }[/math]-function [math]\displaystyle{ F }[/math] is an APN permutation if and only if [1]

[math]\displaystyle{ \sum_{\lambda \in \mathbb{F}_{2^n}^*} \mathcal{F}(D_af_\lambda) = -2^n }[/math]

and

[math]\displaystyle{ \sum_{\lambda \in \mathbb{F}_{2^n}^*} \mathcal{F}^2(D_af_\lambda) = 2^{2n} }[/math]

for any [math]\displaystyle{ a\in\mathbb{F}^*_{2^n} }[/math].

On APN Power Functions

For [math]\displaystyle{ n }[/math] odd, all power APN functions and the known APN binomials are permutations. When [math]\displaystyle{ n }[/math] is even, no APN function exists in a class of permutations including power permutations.

Specifically:

If a power function [math]\displaystyle{ F(x)=x^d }[/math] over [math]\displaystyle{ \mathbb{F}_{2^n} }[/math] is APN, then for every [math]\displaystyle{ x\in \mathbb{F}_{2^n} }[/math] we have [math]\displaystyle{ x^d=1 }[/math] if and only if [math]\displaystyle{ x^3=1 }[/math], that is, [math]\displaystyle{ F^{-1}(1)=\mathbb{F}_4\cap\mathbb{F}_{2^n}^*. }[/math]

If [math]\displaystyle{ n }[/math] is odd, then [math]\displaystyle{ gcd(d,2^n-1)=1 }[/math] and, if [math]\displaystyle{ n }[/math] is even, then [math]\displaystyle{ gcd(d,2^n-1)=3 }[/math].

Consequently, APN power functions are permutations if [math]\displaystyle{ n }[/math] is odd, and are three-to-one over [math]\displaystyle{ \mathbb{F}_{2^n}^* }[/math] if [math]\displaystyle{ n }[/math] is even.[7]

APN Permutations and Codes

Any linear subspace [math]\displaystyle{ C }[/math] of [math]\displaystyle{ \mathbb{F}_2^n }[/math] of dimension [math]\displaystyle{ k }[/math] is called a binary linear code of length [math]\displaystyle{ n }[/math] and dimension [math]\displaystyle{ k }[/math] and is denoted by [math]\displaystyle{ [n,k,d] }[/math], where [math]\displaystyle{ d }[/math] is the minimum Hamming distance of [math]\displaystyle{ C }[/math].

Any linear [math]\displaystyle{ [n,k,d]- }[/math]code [math]\displaystyle{ C }[/math] is associated with its dual [math]\displaystyle{ [n,n-k,d^{\perp}]- }[/math]code, denoted by [math]\displaystyle{ C^{\perp} }[/math] and defined as [math]\displaystyle{ C^{\perp}=\{x\in\mathbb{F}_2^n\;|\;c\cdot x=0, \;\forall c\in C\}. }[/math]

Let [math]\displaystyle{ \mathcal{H} }[/math] be a binary [math]\displaystyle{ (r\times n) }[/math] matrix. We say that a linear binary code [math]\displaystyle{ C }[/math] of length [math]\displaystyle{ n }[/math] is defined by the parity check matrix [math]\displaystyle{ \mathcal{H} }[/math] if [math]\displaystyle{ C=\{c\in\mathbb{F}_2^n\;|\;c\mathcal{H}^t=0\}, }[/math] where [math]\displaystyle{ \mathcal{H}^t }[/math] is the transposed matrix of [math]\displaystyle{ \mathcal{H} }[/math].

APN (and AB) properties were expressed in terms of codes in [8]. In particular, we mention the following result:


Theorem. Let [math]\displaystyle{ F }[/math] be a function on [math]\displaystyle{ \mathbb{F}_{2^m} }[/math] such that [math]\displaystyle{ F(0) = 0 }[/math] and let [math]\displaystyle{ C_F }[/math] be the [math]\displaystyle{ [2^m − 1,k,d]- }[/math]code defined by the parity check matrix

[math]\displaystyle{ \mathcal{H}_F=\begin{pmatrix} 1 & \alpha & \alpha^2 & \cdots & \alpha^{2^m-2}\\ F(1) & F(\alpha) & F(\alpha^2) & \cdots & F(\alpha^{2^m-2}) \end{pmatrix} }[/math]

where each entry is viewed as a binary vector and [math]\displaystyle{ \alpha }[/math] is the primitive element of [math]\displaystyle{ \mathbb{F}_{2^m}. }[/math] Then:

1. The code [math]\displaystyle{ C_F }[/math] is such that [math]\displaystyle{ 3 \leq d \leq 5 }[/math].

2. [math]\displaystyle{ F }[/math] is APN if and only if [math]\displaystyle{ d = 5 }[/math].

3. [math]\displaystyle{ F }[/math] is AB if and only if the weight of every codeword in [math]\displaystyle{ C_F^{\perp} }[/math] lies in [math]\displaystyle{ \{0, 2^{m-1}, 2^{m-1}\pm 2^{m-1/2}\} }[/math].


A binary linear [math]\displaystyle{ [2^k-1,k,2^{k-1}]- }[/math]code [math]\displaystyle{ C }[/math] in [math]\displaystyle{ \mathbb{F}_2^n }[/math] is called simplex. Simplex codes constitute a family of linear error-correcting or error-detecting block codes, easily implemented as polynomial codes (i.e. codes whose encoding and decoding algorithms may be conveniently expressed in terms of polynomials over a base field).

A [math]\displaystyle{ 2k- }[/math]dimensional code [math]\displaystyle{ C }[/math] is called a double simplex code if it can be written as a direct sum of two simplex [math]\displaystyle{ [2^k-1,k,2^{k-1}]- }[/math]codes. The following result provides a connection between APN permutations and double simplex codes:

Theorem.[9] Let [math]\displaystyle{ F:\mathbb{F}_{2^n}\rightarrow\mathbb{F}_{2^n} }[/math] be APN, with [math]\displaystyle{ F(0)=0 }[/math].

[math]\displaystyle{ F }[/math] is CCZ-equivalent to an APN permutation if and only if [math]\displaystyle{ C_F^{\perp} }[/math] is a double simplex code, i.e. [math]\displaystyle{ C_F^{\perp}=C_1\oplus C_2 }[/math], where [math]\displaystyle{ C_1, C_2 }[/math] are simplex [math]\displaystyle{ [2^n-1,n,2^{n-1}]- }[/math]codes.

An APN Permutation in Dimension 6

In his paper [10], Hou conjectured that APN permutations did not exist in even dimension. He proved the following theorem that covers the case of [math]\displaystyle{ n=4 }[/math]:

Let [math]\displaystyle{ F\in\mathbb{F}_{2^n}[x] }[/math] be a permutation polynomial with [math]\displaystyle{ n=2m }[/math]. Then:

1. If [math]\displaystyle{ n=4 }[/math], then [math]\displaystyle{ F }[/math] is not APN.

2. If [math]\displaystyle{ F\in\mathbb{F}_{2^m}[x] }[/math], then [math]\displaystyle{ F }[/math] is not APN.

The question of whether APN permutations exist in even dimension was a long-standing problem until, in 2009, Dillon presented an APN permutation (of algebraic degree [math]\displaystyle{ n-2 }[/math] and nonlinearity [math]\displaystyle{ 2^{n-1}-2^{n/2} }[/math]) in dimension 6[4].

This function is CCZ-equivalent to the Kim function [math]\displaystyle{ \kappa(x)=x^3+x^{10}+ux^{24} }[/math] (where [math]\displaystyle{ u }[/math] is a primitive element of [math]\displaystyle{ \mathbb{F}_{2^6} }[/math]) and it is given by the polynomial

[math]\displaystyle{ g(x)=w^{45}x^{60}+w^{41}x^{58}+w^{43}x^{57}+w^{4}x^{56}+w^{50}x^{54}+w^{20}x^{53}+w^{45}x^{52}+w^{20}x^{51}+w^{23}x^{50}+w^{36}x^{49}+w^{56}x^{48}+w^{21}x^{46}+w^5x^{45}+w^{21}x^{44}+w^{28}x^{43} }[/math]
[math]\displaystyle{ +w^3x^{42}+w^{59}x^{41}+w^{58}x^{40}+w^{57}x^{39}+w^{53}x^{38}+w^{37}x^{37}+w^{40}x^{36}+w^{18}x^{35}+w^{41}x^{34}+w^{54}x^{33}+w^3x^{32}+w^{49}x^{30}+w^{41}x^{29}+w^{42}x^{28} }[/math]
[math]\displaystyle{ +w^{50}x^{27}+w^{53}x^{26}+w^{58}x^{25}+w^9x^{24}+x^{23}+w^{28}x^{22}+w^3x^{21}+w^{21}x^{20}+w^{52}x^{19}+w^{60}x^{17}+w^{59}x^{16}+w^{10}x^{15}+w^{42}x^{13}+w^8x^{12} }[/math]
[math]\displaystyle{ +w^{35}x^{11}+w^{44}x^{10}+w^{45}x^8+w^8x^7+w^{61}x^6+w^{59}x^5+w^{20}x^4+w^{12}x^3+w^{37}x^2+w^2x }[/math]

where [math]\displaystyle{ w=u^{-2} }[/math].

It was used later in the cryptosystem Fides[11], which has been subsequently broken due to its weaknesses in the linear component.

Dillon's function is also EA-equivalent to an involution and it is studied further in the introduction of the butterfly construction[12]. Unfortunately, this construction does not allow obtaining APN permutations in more than six variables[13].

The Big Open APN Problem

The question of existence of APN permutations in even dimension [math]\displaystyle{ n\geq 8 }[/math] remains open. There exist nonexistent results within the following classes:

1. Plateaued functions (when APN, they have bent components);

2. A class of functions including power functions;

3. Functions whose univariate representation coefficients lie in [math]\displaystyle{ \mathbb{F}_{2^{n/2}} }[/math], or in [math]\displaystyle{ \mathbb{F}_{2^4} }[/math] for [math]\displaystyle{ n }[/math] divisible by 4; [10]

4. Functions whose univariate representation coefficients satisfy [math]\displaystyle{ \sum_{i=0}^{(2^n-1)/3}a_{3i}=0 }[/math]; [14]

5. Functions having at least one partially-bent component[6].

References

  1. 1.0 1.1 Thierry Berger, Anne Canteaut, Pascale Charpin, Yann Laigle-Chapuy, On Almost Perfect Nonlinear Functions Over GF(2^n), IEEE Transactions on Information Theory, 2006 Sep,52(9),4160-70
  2. Bartoli, D., Timpanella, M. On a conjecture on APN permutations. Cryptogr. Commun. 14, 925–931 (2022)
  3. Budaghyan, L., Carlet, C., Leander, G.: Two classes of quadratic APN binomials inequivalent to power functions. IEEE Trans. Inf. Theory 54(9), 4218–4229 (2008)
  4. 4.0 4.1 Browning, K., Dillon, J.F., McQuistan, M., Wolfe, A.J.: An APN permutation in dimension six. In: Post-proceedings of the 9-th International conference on Finite Fields and their applications, American Mathematical Society, vol. 518, pp. 33–42 (2010)
  5. Beierle, C., Leander, G.: New instances of quadratic APN functions, arXiv:2009.07204 (2020)
  6. 6.0 6.1 Marco Calderini, Massimiliano Sala, Irene Villa, A note on APN permutations in even dimension, Finite Fields and Their Applications, vol. 46, 1-16, 2017
  7. H. Dobbertin. Private Communication, 1998.
  8. Carlet, Claude & Charpin, Pascale & Zinoviev, Victor. (1998). Codes, Bent Functions and Permutations Suitable For DES-like Cryptosystems. Designs, Codes and Cryptography, vol. 15, p. 125-156.
  9. Browning, K.A. & Dillon, J.F. & Kibler, R.E. & McQuistan, M.T.. (2009). APN polynomials and related codes. Journal of Combinatorics, Information & System Sciences. 34.
  10. 10.0 10.1 X.-D. Hou. Affinity of Permutations of [math]\displaystyle{ \mathbb{F}_2^n }[/math]. Proceedings of Workshop on Coding and Cryptography WCC 2003, pp. 273-280, 2003. Completed version in Discrete Applied Mathematics 154 (2), pp. 313-325, 2006.
  11. B. Bilgin, A. Bogdanov, M. Knezevic, F. Mendel and Q. Wang. Fides: lightweight authenticated cipher with side-channel resistance for constrained hardware. Proceedings of International Workshop Cryptographic Hardware and Embedded Systems CHES 2013, Lecture Notes in Computer Science 8086, pp. 142-158, 2013.
  12. L. Perrin, A. Udovenko, A. Biryukov. Cryptanalysis of a theorem: decomposing the only known solution to the big APN problem. Proceedings of CRYPTO 2016, Lecture Notes in Computer Science 9815, part II, pp. 93-122, 2016.
  13. L. Perrin, A. Canteaut, S. Tian. If a generalized butterfly is APN then it operates on 6 bits. Special Issue on Boolean Functions and Their Applications 2018, Cryptography and Communications 11 (6), pp. 1147-1164, 2019.
  14. A. Canteaut. Differential cryptanalysis of Feistel ciphers and differentially uniform mappings. Proceedings of Selected Areas on Cryptography, SAC 1997, pp. 172-184, 1997.