S-Boxes and Their Algebraic Representations#
- class sage.crypto.sbox.SBox[source]#
Bases:
SageObject
A substitution box or S-box is one of the basic components of symmetric key cryptography. In general, an S-box takes \(m\) input bits and transforms them into \(n\) output bits. This is called an \(m \times n\) S-box and is often implemented as a lookup table. These S-boxes are carefully chosen to resist linear and differential cryptanalysis [He2002].
This module implements an S-box class which allows an algebraic treatment and determine various cryptographic properties.
EXAMPLES:
We consider the S-box of the block cipher PRESENT [BKLPPRSV2007]:
sage: from sage.crypto.sbox import SBox sage: S = SBox(12,5,6,11,9,0,10,13,3,14,15,8,4,7,1,2); S (12, 5, 6, 11, 9, 0, 10, 13, 3, 14, 15, 8, 4, 7, 1, 2) sage: S(1) 5
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(12),Integer(5),Integer(6),Integer(11),Integer(9),Integer(0),Integer(10),Integer(13),Integer(3),Integer(14),Integer(15),Integer(8),Integer(4),Integer(7),Integer(1),Integer(2)); S (12, 5, 6, 11, 9, 0, 10, 13, 3, 14, 15, 8, 4, 7, 1, 2) >>> S(Integer(1)) 5
Note that by default bits are interpreted in big endian order. This is not consistent with the rest of Sage, which has a strong bias towards little endian, but is consistent with most cryptographic literature:
sage: S([0,0,0,1]) [0, 1, 0, 1] sage: S = SBox(12,5,6,11,9,0,10,13,3,14,15,8,4,7,1,2, big_endian=False) sage: S(1) 5 sage: S([0,0,0,1]) [1, 1, 0, 0]
>>> from sage.all import * >>> S([Integer(0),Integer(0),Integer(0),Integer(1)]) [0, 1, 0, 1] >>> S = SBox(Integer(12),Integer(5),Integer(6),Integer(11),Integer(9),Integer(0),Integer(10),Integer(13),Integer(3),Integer(14),Integer(15),Integer(8),Integer(4),Integer(7),Integer(1),Integer(2), big_endian=False) >>> S(Integer(1)) 5 >>> S([Integer(0),Integer(0),Integer(0),Integer(1)]) [1, 1, 0, 0]
Now we construct an
SBox
object for the 4-bit small scale AES S-Box (cf.sage.crypto.mq.sr
):sage: sr = mq.SR(1,1,1,4, allow_zero_inversions=True) sage: S = SBox([sr.sub_byte(e) for e in list(sr.k)]) sage: S (6, 5, 2, 9, 4, 7, 3, 12, 14, 15, 10, 0, 8, 1, 13, 11)
>>> from sage.all import * >>> sr = mq.SR(Integer(1),Integer(1),Integer(1),Integer(4), allow_zero_inversions=True) >>> S = SBox([sr.sub_byte(e) for e in list(sr.k)]) >>> S (6, 5, 2, 9, 4, 7, 3, 12, 14, 15, 10, 0, 8, 1, 13, 11)
AUTHORS:
Rusydi H. Makarim (2016-03-31) : added more functions to determine related cryptographic properties
Yann Laigle-Chapuy (2009-07-01): improve linear and difference matrix computation
Martin R. Albrecht (2008-03-12): initial implementation
REFERENCES:
- autocorrelation_table()[source]#
Return the autocorrelation table corresponding to this S-Box.
for an \(m \times n\) S-Box \(S\), its autocorrelation table entry at row \(a \in \GF{2}^m\) and column \(b \in \GF{2}^n\) (considering their integer representation) is defined as:
\[\sum_{x \in \GF{2}^m} (-1)^{b \cdot S(x) \oplus b \cdot S(x \oplus a)}.\]Equivalently, the columns \(b\) of autocorrelation table correspond to the autocorrelation spectrum of component function \(b \cdot S(x)\).
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: S.autocorrelation_table() # needs sage.combinat [ 8 8 8 8 8 8 8 8] [ 8 0 0 0 0 0 0 -8] [ 8 0 -8 0 0 0 0 0] [ 8 0 0 0 0 -8 0 0] [ 8 -8 0 0 0 0 0 0] [ 8 0 0 0 0 0 -8 0] [ 8 0 0 -8 0 0 0 0] [ 8 0 0 0 -8 0 0 0]
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> S.autocorrelation_table() # needs sage.combinat [ 8 8 8 8 8 8 8 8] [ 8 0 0 0 0 0 0 -8] [ 8 0 -8 0 0 0 0 0] [ 8 0 0 0 0 -8 0 0] [ 8 -8 0 0 0 0 0 0] [ 8 0 0 0 0 0 -8 0] [ 8 0 0 -8 0 0 0 0] [ 8 0 0 0 -8 0 0 0]
- boomerang_connectivity_table()[source]#
Return the boomerang connectivity table (BCT) for this S-Box.
Boomerang connectivity matrix of an invertible \(m \times m\) S-Box \(S\) is an \(2^m \times 2^m\) matrix with entry at row \(\Delta_i \in \GF{2}^m\) and column \(\Delta_o \in \GF{2}^m\) equal to
\[|\{ x \in \GF{2}^m | S^{-1}( S(x) \oplus \Delta_o) \oplus S^{-1}( S(x \oplus \Delta_i) \oplus \Delta_o) = \Delta_i\}|.\]For more results concerning boomerang connectivity matrix, see [CHPSS18]. The algorithm used here is the one from Dunkelman [Du2018].
EXAMPLES:
sage: from sage.crypto.sboxes import PRESENT sage: PRESENT.boomerang_connectivity_table() [16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16] [16 0 4 4 0 16 4 4 4 4 0 0 4 4 0 0] [16 0 0 6 0 4 6 0 0 0 2 0 2 2 2 0] [16 2 0 6 2 4 4 2 0 0 2 2 0 0 0 0] [16 0 0 0 0 4 2 2 0 6 2 0 6 0 2 0] [16 2 0 0 2 4 0 0 0 6 2 2 4 2 0 0] [16 4 2 0 4 0 2 0 2 0 0 4 2 0 4 8] [16 4 2 0 4 0 2 0 2 0 0 4 2 0 4 8] [16 4 0 2 4 0 0 2 0 2 0 4 0 2 4 8] [16 4 2 0 4 0 2 0 2 0 0 4 2 0 4 8] [16 0 2 2 0 4 0 0 6 0 2 0 0 6 2 0] [16 2 0 0 2 4 0 0 4 2 2 2 0 6 0 0] [16 0 6 0 0 4 0 6 2 2 2 0 0 0 2 0] [16 2 4 2 2 4 0 6 0 0 2 2 0 0 0 0] [16 0 2 2 0 0 2 2 2 2 0 0 2 2 0 0] [16 8 0 0 8 0 0 0 0 0 0 8 0 0 8 16]
>>> from sage.all import * >>> from sage.crypto.sboxes import PRESENT >>> PRESENT.boomerang_connectivity_table() [16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16] [16 0 4 4 0 16 4 4 4 4 0 0 4 4 0 0] [16 0 0 6 0 4 6 0 0 0 2 0 2 2 2 0] [16 2 0 6 2 4 4 2 0 0 2 2 0 0 0 0] [16 0 0 0 0 4 2 2 0 6 2 0 6 0 2 0] [16 2 0 0 2 4 0 0 0 6 2 2 4 2 0 0] [16 4 2 0 4 0 2 0 2 0 0 4 2 0 4 8] [16 4 2 0 4 0 2 0 2 0 0 4 2 0 4 8] [16 4 0 2 4 0 0 2 0 2 0 4 0 2 4 8] [16 4 2 0 4 0 2 0 2 0 0 4 2 0 4 8] [16 0 2 2 0 4 0 0 6 0 2 0 0 6 2 0] [16 2 0 0 2 4 0 0 4 2 2 2 0 6 0 0] [16 0 6 0 0 4 0 6 2 2 2 0 0 0 2 0] [16 2 4 2 2 4 0 6 0 0 2 2 0 0 0 0] [16 0 2 2 0 0 2 2 2 2 0 0 2 2 0 0] [16 8 0 0 8 0 0 0 0 0 0 8 0 0 8 16]
- boomerang_uniformity()[source]#
Return the boomerang uniformity
The boomerang uniformity is defined as the highest entry in the boomerang connectivity table, ignoring the first row and column.
EXAMPLES:
sage: from sage.crypto.sboxes import AES sage: AES.boomerang_uniformity() 6
>>> from sage.all import * >>> from sage.crypto.sboxes import AES >>> AES.boomerang_uniformity() 6
- cnf(xi=None, yi=None, format=None)[source]#
Return a representation of this S-Box in conjunctive normal form.
This function examines the truth tables for each output bit of the S-Box and thus has complexity \(n * 2^m\) for an \(m \times n\) S-Box.
INPUT:
xi
– (default:1...m
) indices for the input variablesyi
– (default:m+1 ... m+n
) indices for the output variablesformat
– (default:None
) output format, see below
FORMATS:
None
– return a list of tuples of integers where each tuple represents a clause, the absolute value of an integer represents a variable and the sign of an integer indicates inversionsymbolic
– a string that can be parsed by theSymbolicLogic
packagedimacs
– a string in DIMACS format which is the gold standard for SAT-solver input (cf. http://www.satlib.org/)dimacs_headless
– a string in DIMACS format, but without the header; this is useful for concatenation of outputs
EXAMPLES:
We give a very small example to explain the output format:
sage: from sage.crypto.sbox import SBox sage: S = SBox(1,2,0,3); S (1, 2, 0, 3) sage: cnf = S.cnf(); cnf [(1, 2, -3), (1, 2, 4), (1, -2, 3), (1, -2, -4), (-1, 2, -3), (-1, 2, -4), (-1, -2, 3), (-1, -2, 4)]
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(1),Integer(2),Integer(0),Integer(3)); S (1, 2, 0, 3) >>> cnf = S.cnf(); cnf [(1, 2, -3), (1, 2, 4), (1, -2, 3), (1, -2, -4), (-1, 2, -3), (-1, 2, -4), (-1, -2, 3), (-1, -2, 4)]
This output completely describes the S-Box. For instance, we can check that
S([0,1]) -> [1,0]
satisfies every clause if the first input bit corresponds to the index1
and the last output bit corresponds to the index3
in the output.We can convert this representation to the DIMACS format:
sage: print(S.cnf(format='dimacs')) p cnf 4 8 1 2 -3 0 1 2 4 0 1 -2 3 0 1 -2 -4 0 -1 2 -3 0 -1 2 -4 0 -1 -2 3 0 -1 -2 4 0
>>> from sage.all import * >>> print(S.cnf(format='dimacs')) p cnf 4 8 1 2 -3 0 1 2 4 0 1 -2 3 0 1 -2 -4 0 -1 2 -3 0 -1 2 -4 0 -1 -2 3 0 -1 -2 4 0
For concatenation we can strip the header:
sage: print(S.cnf(format='dimacs_headless')) 1 2 -3 0 1 2 4 0 1 -2 3 0 1 -2 -4 0 -1 2 -3 0 -1 2 -4 0 -1 -2 3 0 -1 -2 4 0
>>> from sage.all import * >>> print(S.cnf(format='dimacs_headless')) 1 2 -3 0 1 2 4 0 1 -2 3 0 1 -2 -4 0 -1 2 -3 0 -1 2 -4 0 -1 -2 3 0 -1 -2 4 0
This might be helpful in combination with the
xi
andyi
parameter to assign indices manually:sage: print(S.cnf(xi=[10,20],yi=[30,40], format='dimacs_headless')) 10 20 -30 0 10 20 40 0 10 -20 30 0 10 -20 -40 0 -10 20 -30 0 -10 20 -40 0 -10 -20 30 0 -10 -20 40 0
>>> from sage.all import * >>> print(S.cnf(xi=[Integer(10),Integer(20)],yi=[Integer(30),Integer(40)], format='dimacs_headless')) 10 20 -30 0 10 20 40 0 10 -20 30 0 10 -20 -40 0 -10 20 -30 0 -10 20 -40 0 -10 -20 30 0 -10 -20 40 0
We can also return a string which is parse-able by the
SymbolicLogic
package:sage: log = SymbolicLogic() sage: s = log.statement(S.cnf(format='symbolic')) sage: log.truthtable(s)[1:] [['False', 'False', 'False', 'False', 'False'], ['False', 'False', 'False', 'True', 'False'], ['False', 'False', 'True', 'False', 'False'], ['False', 'False', 'True', 'True', 'True'], ['False', 'True', 'False', 'False', 'True'], ['False', 'True', 'False', 'True', 'True'], ['False', 'True', 'True', 'False', 'True'], ['False', 'True', 'True', 'True', 'True'], ['True', 'False', 'False', 'False', 'True'], ['True', 'False', 'False', 'True', 'True'], ['True', 'False', 'True', 'False', 'True'], ['True', 'False', 'True', 'True', 'True'], ['True', 'True', 'False', 'False', 'True'], ['True', 'True', 'False', 'True', 'True'], ['True', 'True', 'True', 'False', 'True'], ['True', 'True', 'True', 'True', 'True']]
>>> from sage.all import * >>> log = SymbolicLogic() >>> s = log.statement(S.cnf(format='symbolic')) >>> log.truthtable(s)[Integer(1):] [['False', 'False', 'False', 'False', 'False'], ['False', 'False', 'False', 'True', 'False'], ['False', 'False', 'True', 'False', 'False'], ['False', 'False', 'True', 'True', 'True'], ['False', 'True', 'False', 'False', 'True'], ['False', 'True', 'False', 'True', 'True'], ['False', 'True', 'True', 'False', 'True'], ['False', 'True', 'True', 'True', 'True'], ['True', 'False', 'False', 'False', 'True'], ['True', 'False', 'False', 'True', 'True'], ['True', 'False', 'True', 'False', 'True'], ['True', 'False', 'True', 'True', 'True'], ['True', 'True', 'False', 'False', 'True'], ['True', 'True', 'False', 'True', 'True'], ['True', 'True', 'True', 'False', 'True'], ['True', 'True', 'True', 'True', 'True']]
This function respects endianness of the S-Box:
sage: S = SBox(1,2,0,3, big_endian=False); S (1, 2, 0, 3) sage: cnf = S.cnf(); cnf [(1, 2, -4), (1, 2, 3), (-1, 2, 4), (-1, 2, -3), (1, -2, -4), (1, -2, -3), (-1, -2, 4), (-1, -2, 3)]
>>> from sage.all import * >>> S = SBox(Integer(1),Integer(2),Integer(0),Integer(3), big_endian=False); S (1, 2, 0, 3) >>> cnf = S.cnf(); cnf [(1, 2, -4), (1, 2, 3), (-1, 2, 4), (-1, 2, -3), (1, -2, -4), (1, -2, -3), (-1, -2, 4), (-1, -2, 3)]
S-Boxes with m!=n also work:
sage: o = list(range(8)) + list(range(8)) sage: shuffle(o) sage: S = SBox(o) sage: S.is_permutation() False
sage: len(S.cnf()) == 3*2^4 True
- component_function(b)[source]#
Return a Boolean function corresponding to the component function \(b \cdot S(x)\).
If \(S\) is an \(m \times n\) S-Box, then \(b \in \GF{2}^n\) and \(\cdot\) denotes dot product of two vectors.
INPUT:
b
– either an integer or a list/tuple/vector of \(\GF{2}\) elements of lengthself.output_size()
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([7,6,0,4,2,5,1,3]) sage: f3 = S.component_function(3) sage: f3.algebraic_normal_form() # needs sage.rings.polynomial.pbori x0*x1 + x0*x2 + x0 + x2 sage: f5 = S.component_function([1, 0, 1]) sage: f5.algebraic_normal_form() # needs sage.rings.polynomial.pbori x0*x2 + x0 + x1*x2
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)]) >>> f3 = S.component_function(Integer(3)) >>> f3.algebraic_normal_form() # needs sage.rings.polynomial.pbori x0*x1 + x0*x2 + x0 + x2 >>> f5 = S.component_function([Integer(1), Integer(0), Integer(1)]) >>> f5.algebraic_normal_form() # needs sage.rings.polynomial.pbori x0*x2 + x0 + x1*x2
- derivative(u)[source]#
Return the derivative in direction of
u
INPUT:
u
– either an integer or a tuple/list of \(\GF{2}\) elements of length equal tom
The derivative of \(F\) in direction of \(u\) is defined as \(x \mapsto F(x) + F(x + u)\).
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: s = SBox(0,1,2,3) sage: s.derivative(1) (1, 1, 1, 1) sage: u = [1,0] sage: s.derivative(u) (1, 1, 1, 1) sage: v = vector(GF(2), [1,0]) sage: s.derivative(v) (1, 1, 1, 1) sage: s.derivative(4) Traceback (most recent call last): ... IndexError: list index out of range sage: from sage.crypto.sboxes import PRESENT sage: PRESENT.derivative(1).max_degree() < PRESENT.max_degree() # needs sage.rings.polynomial.pbori True
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> s = SBox(Integer(0),Integer(1),Integer(2),Integer(3)) >>> s.derivative(Integer(1)) (1, 1, 1, 1) >>> u = [Integer(1),Integer(0)] >>> s.derivative(u) (1, 1, 1, 1) >>> v = vector(GF(Integer(2)), [Integer(1),Integer(0)]) >>> s.derivative(v) (1, 1, 1, 1) >>> s.derivative(Integer(4)) Traceback (most recent call last): ... IndexError: list index out of range >>> from sage.crypto.sboxes import PRESENT >>> PRESENT.derivative(Integer(1)).max_degree() < PRESENT.max_degree() # needs sage.rings.polynomial.pbori True
- difference_distribution_table()[source]#
Return difference distribution table (DDT)
A
for this S-box.The rows of
A
encode the differencesDelta I
of the input and the columns encode the differenceDelta O
for the output. The bits are ordered according to the endianess of this S-box. The value atA[Delta I,Delta O]
encodes how oftenDelta O
is the actual output difference givenDelta I
as input difference.See [He2002] for an introduction to differential cryptanalysis.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: S.difference_distribution_table() [8 0 0 0 0 0 0 0] [0 2 2 0 2 0 0 2] [0 0 2 2 0 0 2 2] [0 2 0 2 2 0 2 0] [0 2 0 2 0 2 0 2] [0 0 2 2 2 2 0 0] [0 2 2 0 0 2 2 0] [0 0 0 0 2 2 2 2] sage: S = SBox(7,4,8,6) sage: S.difference_distribution_table() [4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0] [0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 2] [0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0]
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> S.difference_distribution_table() [8 0 0 0 0 0 0 0] [0 2 2 0 2 0 0 2] [0 0 2 2 0 0 2 2] [0 2 0 2 2 0 2 0] [0 2 0 2 0 2 0 2] [0 0 2 2 2 2 0 0] [0 2 2 0 0 2 2 0] [0 0 0 0 2 2 2 2] >>> S = SBox(Integer(7),Integer(4),Integer(8),Integer(6)) >>> S.difference_distribution_table() [4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 2 0 0 0 0 0 0 0 0 0 0 2 0] [0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 2] [0 2 0 0 0 0 0 0 0 0 0 0 2 0 0 0]
- differential_branch_number()[source]#
Return differential branch number of this S-Box.
The differential branch number of an S-Box \(S\) is defined as
\[\min_{v, w \neq v} \{ \mathrm{wt}(v \oplus w) + \mathrm{wt}(S(v) \oplus S(w)) \},\]where \(\mathrm{wt}(x)\) denotes the Hamming weight of vector \(x\).
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([12,5,6,11,9,0,10,13,3,14,15,8,4,7,1,2]) sage: S.differential_branch_number() 3
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(12),Integer(5),Integer(6),Integer(11),Integer(9),Integer(0),Integer(10),Integer(13),Integer(3),Integer(14),Integer(15),Integer(8),Integer(4),Integer(7),Integer(1),Integer(2)]) >>> S.differential_branch_number() 3
- differential_uniformity()[source]#
Return the difference probability of the difference with the highest probability in absolute terms, i.e. how often it occurs in total.
Equivalently, this is equal to the differential uniformity of this S-Box.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: S.maximal_difference_probability_absolute() 2
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> S.maximal_difference_probability_absolute() 2
Note
This code is mainly called internally.
- fixed_points()[source]#
Return a list of all fixed points of this S-Box.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([0,1,3,6,7,4,5,2]) sage: S.fixed_points() [0, 1]
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(0),Integer(1),Integer(3),Integer(6),Integer(7),Integer(4),Integer(5),Integer(2)]) >>> S.fixed_points() [0, 1]
- from_bits(x, n=None)[source]#
Return integer for bitstring
x
of lengthn
.INPUT:
x
– a bitstringn
– bit length (optional)
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: S.from_bits( [1,1,0]) 6 sage: S( S.from_bits( [1,1,0] ) ) 1 sage: S.from_bits( S( [1,1,0] ) ) 1
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> S.from_bits( [Integer(1),Integer(1),Integer(0)]) 6 >>> S( S.from_bits( [Integer(1),Integer(1),Integer(0)] ) ) 1 >>> S.from_bits( S( [Integer(1),Integer(1),Integer(0)] ) ) 1
- has_linear_structure()[source]#
Return
True
if there exists a nonzero component function of this S-Box that has a linear structure.See also
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(12,5,6,11,9,0,10,13,3,14,15,8,4,7,1,2) sage: S.has_linear_structure() True
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(12),Integer(5),Integer(6),Integer(11),Integer(9),Integer(0),Integer(10),Integer(13),Integer(3),Integer(14),Integer(15),Integer(8),Integer(4),Integer(7),Integer(1),Integer(2)) >>> S.has_linear_structure() True
- input_size()[source]#
Return the input size of this S-Box.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([0, 3, 2, 1, 1, 3, 2, 0]) sage: S.input_size() 3
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(0), Integer(3), Integer(2), Integer(1), Integer(1), Integer(3), Integer(2), Integer(0)]) >>> S.input_size() 3
- interpolation_polynomial(k=None)[source]#
Return a univariate polynomial over an extension field representing this S-box.
If
m
is the input length of this S-box then the extension field is of degreem
.If the output length does not match the input length then a
TypeError
is raised.INPUT:
k
– (optional) an instance of \(\GF{2^m}\)
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: f = S.interpolation_polynomial() sage: f (a^2 + a + 1)*x^6 + a^2*x^5 + (a + 1)*x^4 + (a^2 + a)*x^3 + x^2 + a*x + a^2 + a + 1 sage: a = f.base_ring().gen() sage: f(0), S(0) (a^2 + a + 1, 7) sage: f(a^2 + 1), S(5) (a^2 + 1, 5)
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> f = S.interpolation_polynomial() >>> f (a^2 + a + 1)*x^6 + a^2*x^5 + (a + 1)*x^4 + (a^2 + a)*x^3 + x^2 + a*x + a^2 + a + 1 >>> a = f.base_ring().gen() >>> f(Integer(0)), S(Integer(0)) (a^2 + a + 1, 7) >>> f(a**Integer(2) + Integer(1)), S(Integer(5)) (a^2 + 1, 5)
Note
The method-internal call to the S-box initially used a different endianess for handling finite field elements. This changed in Issue #25633, by calling the S-box directly.
- inverse()[source]#
Return the inverse of this S-Box.
Note that the S-Box must be invertible, otherwise it will raise a
TypeError
.EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([0, 1, 3, 6, 7, 4, 5, 2]) sage: Sinv = S.inverse() sage: [Sinv(S(i)) for i in range(8)] [0, 1, 2, 3, 4, 5, 6, 7]
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(0), Integer(1), Integer(3), Integer(6), Integer(7), Integer(4), Integer(5), Integer(2)]) >>> Sinv = S.inverse() >>> [Sinv(S(i)) for i in range(Integer(8))] [0, 1, 2, 3, 4, 5, 6, 7]
- is_almost_bent()[source]#
Return
True
if this S-Box is an almost bent (AB) function.An \(m \times m\) S-Box \(S\), for \(m\) odd, is called almost bent if its nonlinearity is equal to \(2^{m-1} - 2^{(m-1)/2}\).
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([0,1,3,6,7,4,5,2]) sage: S.is_almost_bent() True
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(0),Integer(1),Integer(3),Integer(6),Integer(7),Integer(4),Integer(5),Integer(2)]) >>> S.is_almost_bent() True
- is_apn()[source]#
Return
True
if this S-Box is an almost perfect nonlinear (APN) function.An \(m \times m\) S-Box \(S\) is called almost perfect nonlinear if for every nonzero \(\alpha \in \GF{2}^m\) and every \(\beta \in \GF{2}^m\), the equation \(S(x) \oplus S(x \oplus \alpha) = \beta\) has 0 or 2 solutions. Equivalently, the differential uniformity of \(S\) is equal to 2.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([0,1,3,6,7,4,5,2]) sage: S.is_apn() True sage: S.differential_uniformity() 2
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(0),Integer(1),Integer(3),Integer(6),Integer(7),Integer(4),Integer(5),Integer(2)]) >>> S.is_apn() True >>> S.differential_uniformity() 2
- is_balanced()[source]#
Return
True
if this S-Box is balanced.An S-Box is balanced if all its component functions are balanced.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([12,5,6,11,9,0,10,13,3,14,15,8,4,7,1,2]) sage: S.is_balanced() True
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(12),Integer(5),Integer(6),Integer(11),Integer(9),Integer(0),Integer(10),Integer(13),Integer(3),Integer(14),Integer(15),Integer(8),Integer(4),Integer(7),Integer(1),Integer(2)]) >>> S.is_balanced() True
- is_bent()[source]#
Return
True
if this S-Box is bent, i.e. its nonlinearity is equal to \(2^{m-1} - 2^{m/2 - 1}\) where \(m\) is the input size of the S-Box.EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: R.<x> = GF(2**2, 'a')[] sage: base = R.base_ring() sage: a = base.gen() sage: G = a * x^2 + 1 sage: S = SBox([G(x * y**(14)) for x in sorted(base) for y in sorted(base)]) sage: S.is_bent() True sage: S.nonlinearity() 6 sage: S.linear_approximation_table() [ 8 -2 2 -2] [ 0 -2 2 -2] [ 0 -2 2 -2] [ 0 -2 2 -2] [ 0 -2 2 -2] [ 0 -2 -2 2] [ 0 2 2 2] [ 0 2 -2 -2] [ 0 -2 2 -2] [ 0 2 -2 -2] [ 0 -2 -2 2] [ 0 2 2 2] [ 0 -2 2 -2] [ 0 2 2 2] [ 0 2 -2 -2] [ 0 -2 -2 2]
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> R = GF(Integer(2)**Integer(2), 'a')['x']; (x,) = R._first_ngens(1) >>> base = R.base_ring() >>> a = base.gen() >>> G = a * x**Integer(2) + Integer(1) >>> S = SBox([G(x * y**(Integer(14))) for x in sorted(base) for y in sorted(base)]) >>> S.is_bent() True >>> S.nonlinearity() 6 >>> S.linear_approximation_table() [ 8 -2 2 -2] [ 0 -2 2 -2] [ 0 -2 2 -2] [ 0 -2 2 -2] [ 0 -2 2 -2] [ 0 -2 -2 2] [ 0 2 2 2] [ 0 2 -2 -2] [ 0 -2 2 -2] [ 0 2 -2 -2] [ 0 -2 -2 2] [ 0 2 2 2] [ 0 -2 2 -2] [ 0 2 2 2] [ 0 2 -2 -2] [ 0 -2 -2 2]
- is_involution()[source]#
Return
True
if this S-Box is an involution, i.e. the inverse S-Box is equal itself.EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([x**254 for x in sorted(GF(2**8))]) sage: S.is_involution() True
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([x**Integer(254) for x in sorted(GF(Integer(2)**Integer(8)))]) >>> S.is_involution() True
- is_linear_structure(a, b)[source]#
Return
True
if \(a\) is a linear structure of the component function \(b \cdot S(x)\) where S is this \(m \times n\) S-Box.INPUT:
a
– either an integer or a tuple of \(\GF{2}\) elements of length equal to the input size of SBoxb
– either an integer or a tuple of \(\GF{2}\) elements of length equal to the output size of SBox
See also
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(12,5,6,11,9,0,10,13,3,14,15,8,4,7,1,2) sage: S.component_function(1).autocorrelation() (16, -16, 0, 0, 0, 0, 0, 0, -16, 16, 0, 0, 0, 0, 0, 0) sage: S.is_linear_structure(1, 1) True sage: S.is_linear_structure([1, 0, 0, 1], [0, 0, 0, 1]) True sage: S.is_linear_structure([0, 1, 1, 1], 1) False
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(12),Integer(5),Integer(6),Integer(11),Integer(9),Integer(0),Integer(10),Integer(13),Integer(3),Integer(14),Integer(15),Integer(8),Integer(4),Integer(7),Integer(1),Integer(2)) >>> S.component_function(Integer(1)).autocorrelation() (16, -16, 0, 0, 0, 0, 0, 0, -16, 16, 0, 0, 0, 0, 0, 0) >>> S.is_linear_structure(Integer(1), Integer(1)) True >>> S.is_linear_structure([Integer(1), Integer(0), Integer(0), Integer(1)], [Integer(0), Integer(0), Integer(0), Integer(1)]) True >>> S.is_linear_structure([Integer(0), Integer(1), Integer(1), Integer(1)], Integer(1)) False
- is_monomial_function()[source]#
Return
True
if this S-Box is a monomial/power function.EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([0,1,3,6,7,4,5,2]) sage: S.is_monomial_function() False sage: S_poly = S.interpolation_polynomial(); S_poly (a + 1)*x^6 + (a^2 + a + 1)*x^5 + (a^2 + a)*x^4 + (a^2 + 1)*x^3 + a*x^2 + a*x sage: all([S(x) == S_poly(x) for x in S_poly.base_ring()]) True sage: S = SBox(0,3,2,1) sage: S.interpolation_polynomial() x^2 sage: S.is_monomial_function() True
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(0),Integer(1),Integer(3),Integer(6),Integer(7),Integer(4),Integer(5),Integer(2)]) >>> S.is_monomial_function() False >>> S_poly = S.interpolation_polynomial(); S_poly (a + 1)*x^6 + (a^2 + a + 1)*x^5 + (a^2 + a)*x^4 + (a^2 + 1)*x^3 + a*x^2 + a*x >>> all([S(x) == S_poly(x) for x in S_poly.base_ring()]) True >>> S = SBox(Integer(0),Integer(3),Integer(2),Integer(1)) >>> S.interpolation_polynomial() x^2 >>> S.is_monomial_function() True
- is_permutation()[source]#
Return
True
if this S-Box is a permutation.EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: S.is_permutation() True sage: S = SBox(3,2,0,0,2,1,1,3) sage: S.is_permutation() False
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> S.is_permutation() True >>> S = SBox(Integer(3),Integer(2),Integer(0),Integer(0),Integer(2),Integer(1),Integer(1),Integer(3)) >>> S.is_permutation() False
- is_plateaued()[source]#
Return
True
if this S-Box is plateaued, i.e. for all nonzero \(b \in \GF{2}^n\) the Boolean function \(b \cdot S(x)\) is plateaued.EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(0, 3, 1, 2, 4, 6, 7, 5) sage: S.is_plateaued() True
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(0), Integer(3), Integer(1), Integer(2), Integer(4), Integer(6), Integer(7), Integer(5)) >>> S.is_plateaued() True
- linear_approximation_table(scale='absolute_bias')[source]#
Return linear approximation table (LAT) \(A\) for this S-box.
The entry \(A[\alpha,\beta]\) corresponds to the probability \(Pr[\alpha\cdot x = \beta\cdot S(x)]\), where \(S\) is this S-box mapping \(n\)-bit inputs to \(m\)-bit outputs. There are three typical notations for this probability used in the literature:
\(Pr[\alpha\cdot x = \beta\cdot S(x)] = 1/2 + e(\alpha, \beta)\), where \(e(\alpha, \beta)\) is called the bias,
\(2\cdot Pr[\alpha\cdot x = \beta\cdot S(x)] = 1 + c(\alpha, \beta)\), where \(c(\alpha, \beta) = 2\cdot e(\alpha, \beta)\) is the correlation, and
\(2^{(m+1)}\cdot Pr[\alpha\cdot x = \beta\cdot S(x)] = 2^m + \hat{S}(\alpha, \beta)\), where \(\hat{S}(\alpha, \beta)\) is the Fourier coefficient of S.
See [He2002] for an introduction to linear cryptanalysis.
INPUT:
scale
– string to choose the scaling for the LAT, one of“bias”: elements are \(e(\alpha, \beta)\)
“correlation”: elements are \(c(\alpha, \beta)\)
“absolute_bias”: elements are \(2^m\cdot e(\alpha, \beta)\) (default)
“fourier_coefficient”: elements are \(\hat{S}(\alpha, \beta)\)
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: lat_abs_bias = S.linear_approximation_table() sage: lat_abs_bias [ 4 0 0 0 0 0 0 0] [ 0 0 0 0 2 2 2 -2] [ 0 0 -2 -2 -2 2 0 0] [ 0 0 -2 2 0 0 -2 -2] [ 0 2 0 2 -2 0 2 0] [ 0 -2 0 2 0 2 0 2] [ 0 -2 -2 0 0 -2 2 0] [ 0 -2 2 0 -2 0 0 -2] sage: lat_abs_bias/(1 << S.input_size()) == S.linear_approximation_table(scale="bias") True sage: lat_abs_bias/(1 << (S.input_size()-1)) == S.linear_approximation_table(scale="correlation") True sage: lat_abs_bias*2 == S.linear_approximation_table(scale="fourier_coefficient") True
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> lat_abs_bias = S.linear_approximation_table() >>> lat_abs_bias [ 4 0 0 0 0 0 0 0] [ 0 0 0 0 2 2 2 -2] [ 0 0 -2 -2 -2 2 0 0] [ 0 0 -2 2 0 0 -2 -2] [ 0 2 0 2 -2 0 2 0] [ 0 -2 0 2 0 2 0 2] [ 0 -2 -2 0 0 -2 2 0] [ 0 -2 2 0 -2 0 0 -2] >>> lat_abs_bias/(Integer(1) << S.input_size()) == S.linear_approximation_table(scale="bias") True >>> lat_abs_bias/(Integer(1) << (S.input_size()-Integer(1))) == S.linear_approximation_table(scale="correlation") True >>> lat_abs_bias*Integer(2) == S.linear_approximation_table(scale="fourier_coefficient") True
According to this table the first bit of the input is equal to the third bit of the output 6 out of 8 times:
sage: for i in srange(8): print(S.to_bits(i)[0] == S.to_bits(S(i))[2]) False True True True False True True True
>>> from sage.all import * >>> for i in srange(Integer(8)): print(S.to_bits(i)[Integer(0)] == S.to_bits(S(i))[Integer(2)]) False True True True False True True True
- linear_branch_number()[source]#
Return linear branch number of this S-Box.
The linear branch number of an S-Box \(S\) is defined as
\[\begin{split}\min_{\substack{\alpha \neq 0, \beta \\ \mathrm{LAM}(\alpha, \beta) \neq 0}} \{ \mathrm{wt}(\alpha) + \mathrm{wt}(\beta) \},\end{split}\]where \(\mathrm{LAM}(\alpha, \beta)\) is the entry at row \(\alpha\) and column \(\beta\) of linear approximation matrix correspond to this S-Box. The \(\mathrm{wt}(x)\) denotes the Hamming weight of \(x\).
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([12,5,6,11,9,0,10,13,3,14,15,8,4,7,1,2]) sage: S.linear_branch_number() 2
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(12),Integer(5),Integer(6),Integer(11),Integer(9),Integer(0),Integer(10),Integer(13),Integer(3),Integer(14),Integer(15),Integer(8),Integer(4),Integer(7),Integer(1),Integer(2)]) >>> S.linear_branch_number() 2
- linear_structures()[source]#
Return a list of 3-valued tuple \((b, \alpha, c)\) such that \(\alpha\) is a \(c\)-linear structure of the component function \(b \cdot S(x)\).
A Boolean function \(f : \GF{2}^m \mapsto \GF{2}\) is said to have a \(c\)-linear structure if there exists a nonzero \(\alpha\) such that \(f(x) \oplus f(x \oplus \alpha)\) is a constant function \(c\).
An \(m \times n\) S-Box \(S\) has a linear structure if there exists a component function \(b \cdot S(x)\) that has a linear structure.
The three valued tuple \((b, \alpha, c)\) shows that \(\alpha\) is a \(c\)-linear structure of the component function \(b \cdot S(x)\). This implies that for all output differences \(\beta\) of the S-Box correspond to input difference \(\alpha\), we have \(b \cdot \beta = c\).
See also
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([0,1,3,6,7,4,5,2]) sage: S.linear_structures() # needs sage.combinat [(1, 1, 1), (2, 2, 1), (3, 3, 1), (4, 4, 1), (5, 5, 1), (6, 6, 1), (7, 7, 1)]
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(0),Integer(1),Integer(3),Integer(6),Integer(7),Integer(4),Integer(5),Integer(2)]) >>> S.linear_structures() # needs sage.combinat [(1, 1, 1), (2, 2, 1), (3, 3, 1), (4, 4, 1), (5, 5, 1), (6, 6, 1), (7, 7, 1)]
- linearity()[source]#
Return the linearity of this S-Box.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = mq.SR(1, 4, 4, 8).sbox() sage: S.linearity() 32
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = mq.SR(Integer(1), Integer(4), Integer(4), Integer(8)).sbox() >>> S.linearity() 32
- max_degree()[source]#
Return the maximal algebraic degree of all its component functions.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([12,5,6,11,9,0,10,13,3,14,15,8,4,7,1,2]) sage: S.max_degree() # needs sage.rings.polynomial.pbori 3
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(12),Integer(5),Integer(6),Integer(11),Integer(9),Integer(0),Integer(10),Integer(13),Integer(3),Integer(14),Integer(15),Integer(8),Integer(4),Integer(7),Integer(1),Integer(2)]) >>> S.max_degree() # needs sage.rings.polynomial.pbori 3
- maximal_difference_probability()[source]#
Return the difference probability of the difference with the highest probability in the range between 0.0 and 1.0 indicating 0% or 100% respectively.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: S.maximal_difference_probability() 0.25
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> S.maximal_difference_probability() 0.25
- maximal_difference_probability_absolute()[source]#
Return the difference probability of the difference with the highest probability in absolute terms, i.e. how often it occurs in total.
Equivalently, this is equal to the differential uniformity of this S-Box.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: S.maximal_difference_probability_absolute() 2
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> S.maximal_difference_probability_absolute() 2
Note
This code is mainly called internally.
- maximal_linear_bias_absolute()[source]#
Return maximal linear bias, i.e. how often the linear approximation with the highest bias is true or false minus \(2^{n-1}\).
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: S.maximal_linear_bias_absolute() 2
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> S.maximal_linear_bias_absolute() 2
- maximal_linear_bias_relative()[source]#
Return maximal bias of all linear approximations of this S-box.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: S.maximal_linear_bias_relative() 0.25
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> S.maximal_linear_bias_relative() 0.25
- min_degree()[source]#
Return the minimal algebraic degree of all its component functions.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([12,5,6,11,9,0,10,13,3,14,15,8,4,7,1,2]) sage: S.min_degree() # needs sage.rings.polynomial.pbori 2
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(12),Integer(5),Integer(6),Integer(11),Integer(9),Integer(0),Integer(10),Integer(13),Integer(3),Integer(14),Integer(15),Integer(8),Integer(4),Integer(7),Integer(1),Integer(2)]) >>> S.min_degree() # needs sage.rings.polynomial.pbori 2
- nonlinearity()[source]#
Return the nonlinearity of this S-Box.
The nonlinearity of an S-Box is defined as the minimum nonlinearity of all its component functions.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = mq.SR(1,4,4,8).sbox() sage: S.nonlinearity() 112
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = mq.SR(Integer(1),Integer(4),Integer(4),Integer(8)).sbox() >>> S.nonlinearity() 112
- output_size()[source]#
Return the output size of this S-Box.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([0, 3, 2, 1, 1, 3, 2, 0]) sage: S.output_size() 2
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(0), Integer(3), Integer(2), Integer(1), Integer(1), Integer(3), Integer(2), Integer(0)]) >>> S.output_size() 2
- polynomials(X=None, Y=None, degree=2, groebner=False)[source]#
Return a list of polynomials satisfying this S-box.
First, a simple linear fitting is performed for the given
degree
(cf. for example [BC2003]). Ifgroebner=True
a Groebner basis is also computed for the result of that process.INPUT:
X
– (optional) input variablesY
– (optional) output variablesdegree
– (default:2
) integer > 0groebner
– (default:False
) calculate a reduced Groebner basis of the spanning polynomials to obtain more polynomials
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: P = S.ring()
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> P = S.ring()
By default, this method returns an indirect representation:
sage: S.polynomials() # needs sage.libs.singular [x0*x2 + x1 + y1 + 1, x0*x1 + x1 + x2 + y0 + y1 + y2 + 1, x0*y1 + x0 + x2 + y0 + y2, x0*y0 + x0*y2 + x1 + x2 + y0 + y1 + y2 + 1, x1*x2 + x0 + x1 + x2 + y2 + 1, x0*y0 + x1*y0 + x0 + x2 + y1 + y2, x0*y0 + x1*y1 + x1 + y1 + 1, x1*y2 + x1 + x2 + y0 + y1 + y2 + 1, x0*y0 + x2*y0 + x1 + x2 + y1 + 1, x2*y1 + x0 + y1 + y2, x2*y2 + x1 + y1 + 1, y0*y1 + x0 + x2 + y0 + y1 + y2, y0*y2 + x1 + x2 + y0 + y1 + 1, y1*y2 + x2 + y0]
>>> from sage.all import * >>> S.polynomials() # needs sage.libs.singular [x0*x2 + x1 + y1 + 1, x0*x1 + x1 + x2 + y0 + y1 + y2 + 1, x0*y1 + x0 + x2 + y0 + y2, x0*y0 + x0*y2 + x1 + x2 + y0 + y1 + y2 + 1, x1*x2 + x0 + x1 + x2 + y2 + 1, x0*y0 + x1*y0 + x0 + x2 + y1 + y2, x0*y0 + x1*y1 + x1 + y1 + 1, x1*y2 + x1 + x2 + y0 + y1 + y2 + 1, x0*y0 + x2*y0 + x1 + x2 + y1 + 1, x2*y1 + x0 + y1 + y2, x2*y2 + x1 + y1 + 1, y0*y1 + x0 + x2 + y0 + y1 + y2, y0*y2 + x1 + x2 + y0 + y1 + 1, y1*y2 + x2 + y0]
We can get a direct representation by computing a lexicographical Groebner basis with respect to the right variable ordering, i.e. a variable ordering where the output bits are greater than the input bits:
sage: P.<y0,y1,y2,x0,x1,x2> = PolynomialRing(GF(2),6,order='lex') sage: S.polynomials([x0,x1,x2],[y0,y1,y2], groebner=True) # needs sage.libs.singular [y0 + x0*x1 + x0*x2 + x0 + x1*x2 + x1 + 1, y1 + x0*x2 + x1 + 1, y2 + x0 + x1*x2 + x1 + x2 + 1]
>>> from sage.all import * >>> P = PolynomialRing(GF(Integer(2)),Integer(6),order='lex', names=('y0', 'y1', 'y2', 'x0', 'x1', 'x2',)); (y0, y1, y2, x0, x1, x2,) = P._first_ngens(6) >>> S.polynomials([x0,x1,x2],[y0,y1,y2], groebner=True) # needs sage.libs.singular [y0 + x0*x1 + x0*x2 + x0 + x1*x2 + x1 + 1, y1 + x0*x2 + x1 + 1, y2 + x0 + x1*x2 + x1 + x2 + 1]
- ring()[source]#
Create, return, and cache a polynomial ring for S-box polynomials.
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: S.ring() Multivariate Polynomial Ring in x0, x1, x2, y0, y1, y2 over Finite Field of size 2
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> S.ring() Multivariate Polynomial Ring in x0, x1, x2, y0, y1, y2 over Finite Field of size 2
- solutions(X=None, Y=None)[source]#
Return a dictionary of solutions to this S-box.
INPUT:
X
– (optional) input variablesY
– (optional) output variables
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox([7,6,0,4,2,5,1,3]) sage: F = S.polynomials() # needs sage.libs.singular sage: s = S.solutions() sage: any(f.subs(_s) for f in F for _s in s) # needs sage.libs.singular False
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox([Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)]) >>> F = S.polynomials() # needs sage.libs.singular >>> s = S.solutions() >>> any(f.subs(_s) for f in F for _s in s) # needs sage.libs.singular False
- to_bits(x, n=None)[source]#
Return bitstring of length
n
for integerx
. The returned bitstring is guaranteed to have lengthn
.INPUT:
x
– an integern
– bit length (optional)
EXAMPLES:
sage: from sage.crypto.sbox import SBox sage: S = SBox(7,6,0,4,2,5,1,3) sage: S.to_bits(6) [1, 1, 0] sage: S.to_bits( S(6) ) [0, 0, 1] sage: S( S.to_bits( 6 ) ) [0, 0, 1]
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S = SBox(Integer(7),Integer(6),Integer(0),Integer(4),Integer(2),Integer(5),Integer(1),Integer(3)) >>> S.to_bits(Integer(6)) [1, 1, 0] >>> S.to_bits( S(Integer(6)) ) [0, 0, 1] >>> S( S.to_bits( Integer(6) ) ) [0, 0, 1]
- sage.crypto.sbox.feistel_construction(*args)[source]#
Return an S-Box constructed by Feistel structure using smaller S-Boxes in
args
. The number of round in the construction is equal to the number of S-Boxes provided as input. For more results concerning the differential uniformity and the nonlinearity of S-Boxes constructed by Feistel structures see [CDL2015].INPUT:
args
– a finite iterable SBox objects
EXAMPLES:
Suppose we construct an \(8 \times 8\) S-Box with 3-round Feistel construction from the S-Box of PRESENT:
sage: from sage.crypto.sbox import SBox sage: s = SBox(12,5,6,11,9,0,10,13,3,14,15,8,4,7,1,2) sage: from sage.crypto.sbox import feistel_construction sage: S = feistel_construction(s, s, s)
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> s = SBox(Integer(12),Integer(5),Integer(6),Integer(11),Integer(9),Integer(0),Integer(10),Integer(13),Integer(3),Integer(14),Integer(15),Integer(8),Integer(4),Integer(7),Integer(1),Integer(2)) >>> from sage.crypto.sbox import feistel_construction >>> S = feistel_construction(s, s, s)
The properties of the constructed S-Box can be easily examined:
sage: S.nonlinearity() 96 sage: S.differential_branch_number() 2 sage: S.linear_branch_number() 2
>>> from sage.all import * >>> S.nonlinearity() 96 >>> S.differential_branch_number() 2 >>> S.linear_branch_number() 2
- sage.crypto.sbox.misty_construction(*args)[source]#
Return an S-Box constructed by MISTY structure using smaller S-Boxes in
args
.The number of round in the construction is equal to the number of S-Boxes provided as input. For further result related to the nonlinearity and differential uniformity of the constructed S-Box one may consult [CDL2015].
INPUT:
args
– a finite iterable SBox objects
EXAMPLES:
We construct an \(8 \times 8\) S-Box using 3-round MISTY structure with the following \(4 \times 4\) S-Boxes \(S1, S2, S3\) (see Example 2 in [CDL2015]):
sage: from sage.crypto.sbox import SBox sage: S1 = SBox([0x4,0x0,0x1,0xF,0x2,0xB,0x6,0x7,0x3,0x9,0xA,0x5,0xC,0xD,0xE,0x8]) sage: S2 = SBox([0x0,0x0,0x0,0x1,0x0,0xA,0x8,0x3,0x0,0x8,0x2,0xB,0x4,0x6,0xE,0xD]) sage: S3 = SBox([0x0,0x7,0xB,0xD,0x4,0x1,0xB,0xF,0x1,0x2,0xC,0xE,0xD,0xC,0x5,0x5]) sage: from sage.crypto.sbox import misty_construction sage: S = misty_construction(S1, S2, S3)
>>> from sage.all import * >>> from sage.crypto.sbox import SBox >>> S1 = SBox([Integer(0x4),Integer(0x0),Integer(0x1),Integer(0xF),Integer(0x2),Integer(0xB),Integer(0x6),Integer(0x7),Integer(0x3),Integer(0x9),Integer(0xA),Integer(0x5),Integer(0xC),Integer(0xD),Integer(0xE),Integer(0x8)]) >>> S2 = SBox([Integer(0x0),Integer(0x0),Integer(0x0),Integer(0x1),Integer(0x0),Integer(0xA),Integer(0x8),Integer(0x3),Integer(0x0),Integer(0x8),Integer(0x2),Integer(0xB),Integer(0x4),Integer(0x6),Integer(0xE),Integer(0xD)]) >>> S3 = SBox([Integer(0x0),Integer(0x7),Integer(0xB),Integer(0xD),Integer(0x4),Integer(0x1),Integer(0xB),Integer(0xF),Integer(0x1),Integer(0x2),Integer(0xC),Integer(0xE),Integer(0xD),Integer(0xC),Integer(0x5),Integer(0x5)]) >>> from sage.crypto.sbox import misty_construction >>> S = misty_construction(S1, S2, S3)
The properties of the constructed S-Box can be easily examined:
sage: S.differential_uniformity() 8 sage: S.linearity() 64
>>> from sage.all import * >>> S.differential_uniformity() 8 >>> S.linearity() 64