.. _chapter-codes:
************************
Linear codes and ciphers
************************
Codes
=====
A linear code of length :math:`n` is a finite dimensional
subspace of :math:`GF(q)^n`. Sage can compute with linear
error-correcting codes to a limited extent. It basically has some
wrappers to GAP and GUAVA commands. GUAVA 2.8 is not included
with Sage 4.0's install of GAP but can be installed as an optional
package.
.. index:
pair: codes; linear
pair: codes; Hamming
Sage can compute Hamming codes
::
sage: C = codes.HammingCode(GF(3), 3)
sage: C
[13, 10] Hamming Code over GF(3)
sage: C.minimum_distance()
3
sage: C.generator_matrix()
[1 0 0 0 0 0 0 0 0 0 1 2 0]
[0 1 0 0 0 0 0 0 0 0 0 1 2]
[0 0 1 0 0 0 0 0 0 0 1 0 2]
[0 0 0 1 0 0 0 0 0 0 1 1 1]
[0 0 0 0 1 0 0 0 0 0 1 1 2]
[0 0 0 0 0 1 0 0 0 0 2 0 2]
[0 0 0 0 0 0 1 0 0 0 1 2 1]
[0 0 0 0 0 0 0 1 0 0 2 1 1]
[0 0 0 0 0 0 0 0 1 0 2 2 0]
[0 0 0 0 0 0 0 0 0 1 0 1 1]
.. index::
pair: codes; Golay
the four Golay codes
::
sage: C = codes.GolayCode(GF(3))
sage: C
[12, 6, 6] Extended Golay code over GF(3)
sage: C.minimum_distance()
6
sage: C.generator_matrix()
[1 0 0 0 0 0 2 0 1 2 1 2]
[0 1 0 0 0 0 1 2 2 2 1 0]
[0 0 1 0 0 0 1 1 1 0 1 1]
[0 0 0 1 0 0 1 1 0 2 2 2]
[0 0 0 0 1 0 2 1 2 2 0 1]
[0 0 0 0 0 1 0 2 1 2 2 1]
as well as binary Reed-Muller codes, quadratic residue codes,
quasi-quadratic residue codes, "random" linear codes, and a code
generated by a matrix of full rank (using, as usual, the rows as
the basis).
.. index::
pair: codes; check matrix
pair: codes; generator matrix
pair: codes; dual
For a given code, :math:`C`, Sage can return a generator matrix,
a check matrix, and the dual code:
::
sage: C = codes.HammingCode(GF(2), 3)
sage: Cperp = C.dual_code()
sage: C; Cperp
[7, 4] Hamming Code over GF(2)
[7, 3] linear code over GF(2)
sage: C.generator_matrix()
[1 0 0 0 0 1 1]
[0 1 0 0 1 0 1]
[0 0 1 0 1 1 0]
[0 0 0 1 1 1 1]
sage: C.parity_check_matrix()
[1 0 1 0 1 0 1]
[0 1 1 0 0 1 1]
[0 0 0 1 1 1 1]
sage: C.dual_code()
[7, 3] linear code over GF(2)
sage: C = codes.HammingCode(GF(4,'a'), 3)
sage: C.dual_code()
[21, 3] linear code over GF(4)
For :math:`C` and a vector :math:`v\in GF(q)^n`, Sage can try
to decode :math:`v` (i.e., find the codeword :math:`c\in C`
closest to :math:`v` in the Hamming metric) using syndrome
decoding. As of yet, no special decoding methods have been
implemented.
::
sage: C = codes.HammingCode(GF(2), 3)
sage: MS = MatrixSpace(GF(2),1,7)
sage: F = GF(2); a = F.gen()
sage: v = vector([a,a,F(0),a,a,F(0),a])
sage: c = C.decode_to_code(v, "Syndrome"); c
(1, 1, 0, 1, 0, 0, 1)
sage: c in C
True
To plot the (histogram of) the weight distribution of a code, one
can use the matplotlib package included with Sage:
::
sage: C = codes.HammingCode(GF(2), 4)
sage: C
[15, 11] Hamming Code over GF(2)
sage: w = C.weight_distribution(); w
[1, 0, 0, 35, 105, 168, 280, 435, 435, 280, 168, 105, 35, 0, 0, 1]
sage: J = range(len(w))
sage: W = IndexedSequence([ZZ(w[i]) for i in J],J)
sage: P = W.plot_histogram()
Now type ``show(P)`` to view this.
There are several coding theory functions we are skipping entirely.
Please see the reference manual or the file
``coding/linear_codes.py`` for examples.
Sage can also compute algebraic-geometric codes, called AG codes,
via the Singular interface ยง sec:agcodes. One may also use the AG
codes implemented in GUAVA via the Sage interface to GAP
``gap_console()``. See the GUAVA manual for more details. {GUAVA}
Ciphers
=======
LFSRs
-----
A special type of stream cipher is implemented in Sage, namely, a
linear feedback shift register (LFSR) sequence defined over a
finite field. Stream ciphers have been used for a long time as a
source of pseudo-random number generators.
{linear feedback shift register}
S. Golomb {G} gives a list of three statistical properties a
sequence of numbers :math:`{\bf a}=\{a_n\}_{n=1}^\infty`,
:math:`a_n\in \{0,1\}`, should display to be considered "random".
Define the autocorrelation of :math:`{\bf a}` to be
.. math::
C(k)=C(k,{\bf a})=\lim_{N\rightarrow \infty}
\frac{1}{N}\sum_{n=1}^N (-1)^{a_n+a_{n+k}}.
In the case where :math:`a` is periodic with period
:math:`P` then this reduces to
.. math::C(k)=\frac{1}{P}\sum_{n=1}^P (-1)^{a_n+a_{n+k}}.
Assume :math:`a` is periodic with period :math:`P`.
- balance: :math:`|\sum_{n=1}^P(-1)^{a_n}|\leq 1`.
- low autocorrelation:
.. math::
C(k)=
\left\{
\begin{array}{cc}
1,& k=0,\\
\epsilon, & k\not= 0.
\end{array}
\right.
(For sequences satisfying these first two properties, it is known
that :math:`\epsilon=-1/P` must hold.)
- proportional runs property: In each period, half the runs have
length :math:`1`, one-fourth have length :math:`2`, etc.
Moveover, there are as many runs of :math:`1`'s as there are of
:math:`0`'s.
A sequence satisfying these properties will be called
pseudo-random. {pseudo-random}
A general feedback shift register is a map
:math:`f:{\bf F}_q^d\rightarrow {\bf F}_q^d` of the form
.. MATH::
\begin{array}{c}
f(x_0,...,x_{n-1})=(x_1,x_2,...,x_n),\\
x_n=C(x_0,...,x_{n-1}),
\end{array}
where :math:`C:{\bf F}_q^d\rightarrow {\bf F}_q` is a given
function. When :math:`C` is of the form
.. MATH::
C(x_0,...,x_{n-1}) = c_0 x_0 + ... + c_{n-1} x_{n-1},
for some given constants :math:`c_i\in {\bf F}_q`, the map is
called a linear feedback shift register (LFSR). The sequence of
coefficients :math:`c_i` is called the key and the polynomial
.. MATH::
C(x) = 1+ c_0x +...+c_{n-1}x^n
.. index::
pair: ciphers; connection polynomial
is sometimes called the connection polynomial.
Example: Over :math:`GF(2)`, if
:math:`[c_0,c_1,c_2,c_3]=[1,0,0,1]` then
:math:`C(x) = 1 + x + x^4`,
.. math::x_n = x_{n-4} + x_{n-1},\ \ \ n\geq 4.
The LFSR sequence is then
.. math::
\begin{array}{c}
1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, \\
1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, ...\ .
\end{array}
The sequence of :math:`0,1`'s is periodic with period
:math:`P=2^4-1=15` and satisfies Golomb's three randomness
conditions. However, this sequence of period 15 can be "cracked"
(i.e., a procedure to reproduce :math:`g(x)`) by knowing only 8
terms! This is the function of the Berlekamp-Massey algorithm {M},
implemented as ``lfsr_connection_polynomial`` (which produces the
reverse of ``berlekamp_massey``).
::
sage: F = GF(2)
sage: o = F(0)
sage: l = F(1)
sage: key = [l,o,o,l]; fill = [l,l,o,l]; n = 20
sage: s = lfsr_sequence(key,fill,n); s
[1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0]
sage: lfsr_autocorrelation(s,15,7)
4/15
sage: lfsr_autocorrelation(s,15,0)
8/15
sage: lfsr_connection_polynomial(s)
x^4 + x + 1
sage: from sage.matrix.berlekamp_massey import berlekamp_massey
sage: berlekamp_massey(s)
x^4 + x^3 + 1
Classical ciphers
-----------------
has a type for cryptosystems (created by David Kohel, who also
wrote the examples below), implementing classical cryptosystems.
The general interface is as follows:
::
sage: S = AlphabeticStrings()
sage: S
Free alphabetic string monoid on A-Z
sage: E = SubstitutionCryptosystem(S)
sage: E
Substitution cryptosystem on Free alphabetic string monoid on A-Z
sage: K = S([ 25-i for i in range(26) ])
sage: e = E(K)
sage: m = S("THECATINTHEHAT")
sage: e(m)
GSVXZGRMGSVSZG
Here's another example:
::
sage: S = AlphabeticStrings()
sage: E = TranspositionCryptosystem(S,15);
sage: m = S("THECATANDTHEHAT")
sage: G = E.key_space()
sage: G
Symmetric group of order 15! as a permutation group
sage: g = G([ 3, 2, 1, 6, 5, 4, 9, 8, 7, 12, 11, 10, 15, 14, 13 ])
sage: e = E(g)
sage: e(m)
EHTTACDNAEHTTAH
The idea is that a cryptosystem is a map
:math:`E: KS \to \text{Hom}_\text{Set}(MS,CS)` where
:math:`KS`, :math:`MS`, and :math:`CS` are the key space,
plaintext (or message) space, and ciphertext space, respectively.
:math:`E` is presumed to be injective, so ``e.key()`` returns the
pre-image key.