public Matrix GetBasisOfWeight(Matrix B, int weight, int num)
{
Matrix res = new Matrix(), Bchange, B_copy = new Matrix(B);
while (res.size[0] < num)
{
Bchange = MatrixFuncs.GenNoise(B.size[0]);
B_copy = Bchange * B_copy;
for (int i = 0; i < B.size[0]; ++i)
{
if (Common.wt(B_copy.data[i]) == weight)
{
if (MatrixFuncs.Gauss(res & new Vector(B_copy.data[i])) == res.size[0] + 1)
{
;
}
res &= new Vector(B_copy.data[i]);
}
if (res.size[0] == num)
{
break;
}
}
}
return(res);
}
public static Matrix operator *(Code C1, Code C2)
{
if (C1.n != C2.n)
{
return(null);
}
List <List <int> > new_basis = new List <List <int> >();
List <int> item = new List <int>();
for (int i = 0; i < C1.k; ++i)
{
for (int j = 0; j < C2.k; ++j)
{
item = new List <int>();
for (int s = 0; s < C2.n; ++s)
{
item.Add(C1.G.data[i][s] * C2.G.data[j][s]);
}
new_basis.Add(item);
}
}
Matrix res = new Matrix(new_basis);
MatrixFuncs.Gauss(res);
return(res);
}
bool checkP(Matrix Gp, Matrix P1_inv, Ham ham, Matrix Zero, int s, int n)
{
bool result = true;
for (int i = 0; i < s - 1; ++i)
{
result &= MatrixFuncs.SubMatrix(Gp * P1_inv, i * n, (i + 1) * n) * MatrixFuncs.Transp(ham.H) == Zero;
}
return(result);
}
// Find A^{-1}
public static Matrix Invert(Matrix A)
{
Matrix E = new Matrix(A.size[0], A.size[0]);
for (int i = 0; i < A.size[0]; ++i)
{
E.data[i][i] = 1;
}
return(MatrixFuncs.SolveEq(A, E));
}
public Matrix R; // secret key
public double KeyGen(CodeType codetype, int[] param)
{
Code code = new Code();
int k = 0, n = 0, r, m, l = param[2];
switch (codetype)
{
case CodeType.Hamming:
r = param[0];
code = new Ham(r);
break;
case CodeType.RM:
r = param[0]; m = param[1];
code = new RM(r, m);
break;
}
k = code.G.size[0]; n = code.G.size[1];
Stopwatch t = new Stopwatch(); t.Start();
//Matrix N
N = MatrixFuncs.GenNoise(k);
//Matrix P
int nn = n + l; P = new Matrix(nn, nn);
int[] check = new int[nn]; int ind = 0;
for (int i = 0; i < nn; ++i)
{
do
{
ind = Common.GetRand() % nn;
} while (check[ind] == 1);
P.data[ind][i] = 1;
check[ind] = 1;
}
//Matrix R
R = new Matrix(k, l);
for (int i = 0; i < k; ++i)
{
for (int j = 0; j < l; ++j)
{
R.data[i][j] = Common.GetRand() & 1;
}
}
Gp = N * (code.G | R) * P;
t.Stop();
return(t.ElapsedMilliseconds / 1000.00);
}
public Matrix P; // secret key
public double KeyGen(CodeType codetype, int[] param)
{
Code code = new Code();
int k, n, r = 0, s = 0, m, nn;
switch (codetype)
{
case CodeType.Hamming:
r = param[0];
s = param[1];
code = new Ham(r);
break;
case CodeType.RM:
r = param[0]; m = param[1]; s = param[2];
code = new RM(r, m);
break;
}
k = code.G.size[0]; n = code.G.size[1]; nn = n * s;
Stopwatch t = new Stopwatch(); t.Start();
//Matrix list N
N = new List <Matrix>();
Matrix N_i, NG = new Matrix();
for (int ii = 0; ii < s; ++ii)
{
N_i = MatrixFuncs.GenNoise(k);
N.Add(N_i);
NG |= N_i * code.G;
}
//Matrix P
P = new Matrix(nn, nn);
int[] check = new int[nn]; int ind = 0;
for (int i = 0; i < nn; ++i)
{
do
{
ind = Common.GetRand() % nn;
} while (check[ind] == 1);
P.data[ind][i] = 1;
check[ind] = 1;
}
Gp = NG * P;
t.Stop();
return(t.ElapsedMilliseconds / 1000.00);
}
// Generate a random invertible matrix
public static Matrix GenNoise(int size)
{
Matrix res = new Matrix(size, size);
do
{
for (int i = 0; i < size; ++i)
{
for (int j = 0; j < size; ++j)
{
res.data[i][j] = Common.GetRand() & 1;
}
}
} while (MatrixFuncs.Gauss(new Matrix(res)) < size);
return(res);
}
public static Matrix DualMatrix(Matrix G1)
{
Matrix G1_copy = new Matrix(G1);
List <int> I, J; int k = G1_copy.size[0], n = G1_copy.size[1];
Matrix H1 = new Matrix(n - k, n);
MatrixFuncs.Gauss_E(G1_copy, out I, out J);
for (int s = 0; s < k; ++s)
{
for (int i = 0; i < n - k; ++i)
{
H1.data[i][I[s]] = G1_copy.data[s][J[i]];
}
}
for (int i = 0; i < n - k; ++i)
{
H1.data[i][J[i]] = 1;
}
return(H1);
}
public Matrix P; // secret key
public double KeyGen(CodeType codetype, int[] param)
{
Code code = new Code();
int k = 0, n = 0, r, m;
switch (codetype)
{
case CodeType.Hamming:
r = param[0];
code = new Ham(r);
break;
case CodeType.RM:
r = param[0]; m = param[1];
code = new RM(r, m);
break;
}
k = code.G.size[0]; n = code.G.size[1];
Stopwatch t = new Stopwatch(); t.Start();
//Matrix N
N = MatrixFuncs.GenNoise(k);
//Matrix P
P = new Matrix(n, n);
int[] check = new int[n]; int ind = 0;
for (int i = 0; i < n; ++i)
{
do
{
ind = Common.GetRand() % n;
} while (check[ind] == 1);
P.data[ind][i] = 1;
check[ind] = 1;
}
Gp = N * code.G * P;
t.Stop();
return(t.ElapsedMilliseconds / 1000.00);
}
public double AttackHam(out Matrix N1, out Matrix P1)
{
int k = Gp.size[0], n = Gp.size[1];
N1 = new Matrix(k, k); P1 = new Matrix(n, n);
Code code = new Code(Gp);
// compute r
int r = 0;
while ((1 << r) - 1 < n)
{
++r;
}
Stopwatch t = new Stopwatch(); t.Start();
// Matrix P
Ham ham = new Ham(r);
IEnumerable <int> tmp1, tmp2;
Matrix P1_inv = new Matrix(n, n);
for (int j = 0; j < n; ++j)
{
tmp1 = code.H.data.Select(x => x[j]);
for (int jj = 0; jj < n; ++jj)
{
tmp2 = ham.H.data.Select(x => x[jj]);
if (tmp1.SequenceEqual(tmp2))
{
P1.data[jj][j] = 1;
P1_inv.data[j][jj] = 1;
break;
}
}
}
// Matrix N
code.G = code.G * P1_inv;
N1 = MatrixFuncs.Transp(MatrixFuncs.SolveEq(MatrixFuncs.Transp(ham.G), MatrixFuncs.Transp(code.G)));
t.Stop();
return(t.ElapsedMilliseconds / 1000.00);
}
public List <int>[] GetHamIndices(Code code, Ham ham, int r, int s, int n, int k)
{
int hweight = 1 << (r - 1);
Matrix Bchange = MatrixFuncs.GenNoise(n * s - k), Hsub = GetBasisOfWeight(code.H, s * hweight, n - k);
IEnumerable <int> hcol1, hcol2;
List <int> check = Enumerable.Range(0, n * s).ToList();
List <int>[] res_idx = new List <int> [n];
for (int j = 0; j < n; ++j)
{
res_idx[j] = new List <int>();
hcol1 = ham.H.data.Select(x => x[j]);
for (int jj = 0; jj < check.Count; ++jj)
{
hcol2 = Hsub.data.Select(x => x[check[jj]]);
if (hcol2.SequenceEqual(hcol1))
{
res_idx[j].Add(check[jj]);
check.RemoveAt(jj);
--jj;
}
if (res_idx[j].Count > s)
{
break;
}
}
if (res_idx[j].Count != s)
{
Hsub = GetBasisOfWeight(code.H, s * hweight, n - k);
res_idx = new List <int> [n];
check = Enumerable.Range(0, n * s).ToList();
j = -1;
}
}
return(res_idx);
}
// Find vector by weight in a code
public static Vector FindWeight_simple(Matrix G1, int w)
{
int tmp, k = G1.size[0], n = G1.size[1];
List <int> I = new List <int>(), J = new List <int>(); int[] check;
Random rnd = new Random();
while (true)
{
check = new int[n];
while (I.Count < k)
{
tmp = Math.Abs(Common.GetRand()) % n; // rnd.Next(0, n);
if (check[tmp] == 0)
{
I.Add(tmp);
check[tmp] = 1;
}
}
for (int i = 0; i < check.Length; ++i)
{
if (check[i] == 0)
{
J.Add(i);
}
}
MatrixFuncs.Gauss_on_I(G1, I, J);
for (int i = 0; i < G1.size[0]; ++i)
{
if (Common.wt(G1.data[i]) <= w)
{
return(new Vector(G1.data[i]));
}
}
I.Clear(); J.Clear();
}
}
public double AttackHam(out List <Matrix> Nlist, out Matrix P1)
{
int k = Gp.size[0], nn = Gp.size[1];
Nlist = new List <Matrix>(); P1 = new Matrix(nn, nn);
int r = (int)Math.Log((nn + 2) / 2, 2);
int tmp = nn % ((1 << r) - 1), s;
while (tmp != 0)
{
--r;
tmp = nn % ((1 << r) - 1);
}
s = nn / ((1 << r) - 1); int n = nn / s;
Matrix Ni = new Matrix(k, k); P1 = new Matrix(nn, nn); Matrix P1_inv = new Matrix(nn, nn);
Code code = new Code(Gp);
Ham ham = new Ham(r);
Stopwatch t = new Stopwatch(); t.Start();
// Matrix P1
List <int>[] ham_idx = GetHamIndices(code, ham, r, s, n, k);
Matrix Zero = new Matrix(k, n - k);
BigInteger iter_count = 0, max_iter_num = 1, ind_count = 0;
List <int>[] idx_copy = new List <int> [n]; int[][] indices = new int[s][];
for (int i = 0; i < s; ++i)
{
indices[i] = new int[n];
max_iter_num = BigInteger.Multiply(max_iter_num, BigInteger.Pow(s - i, n));
}
do
{
++iter_count; ++ind_count;
if (iter_count > max_iter_num)
{
ham_idx = GetHamIndices(code, ham, r, s, n, k);
for (int i = 0; i < s; ++i)
{
indices[i] = new int[n];
}
iter_count = 1; ind_count = 1;
}
idx_copy = ham_idx.Select(x => new List <int>(x)).ToArray();
P1 = new Matrix(nn, nn); P1_inv = new Matrix(nn, nn);
for (int i = 0; i < s; i++)
{
for (int j = 0; j < n; ++j)
{
P1.data[i * n + j][idx_copy[j][indices[i][j]]] = 1;
P1_inv.data[idx_copy[j][indices[i][j]]][i * n + j] = 1;
idx_copy[j].RemoveAt(indices[i][j]);
}
}
Common.NextSet(indices[0], s, n);
if (ind_count == BigInteger.Pow(s, n))
{
indices[0] = new int[n];
Common.NextSet(indices[1], s - 1, n);
ind_count = 0;
}
} while (checkP(Gp, P1_inv, ham, Zero, s, n) == false);
// Matrices N
Matrix NG = Gp * P1_inv;
for (int i = 0; i < s; ++i)
{
Ni = MatrixFuncs.SolveEq(MatrixFuncs.Transp(ham.G), MatrixFuncs.Transp(MatrixFuncs.SubMatrix(NG, i * n, (i + 1) * n)));
var ttt = MatrixFuncs.Transp(Ni) * ham.G == MatrixFuncs.SubMatrix(NG, i * n, (i + 1) * n);
Nlist.Add(MatrixFuncs.Transp(Ni));
}
NG = new Matrix();
for (int i = 0; i < Nlist.Count; ++i)
{
NG |= Nlist[i] * ham.G;
}
t.Stop();
return(t.ElapsedMilliseconds / 1000.00);
}
// Reduction on r-parameter (for RM-codes)
public static Code Reduction(Code code_r, int r, int m)
{
int k = code_r.G.size[0], n = code_r.G.size[1];
Matrix res = new Matrix();
int sz = code_r.G.size[0] - Common.C(m, r);
Vector x; List <int> ind_f = new List <int>(); List <List <int> > ind_sets = new List <List <int> >();
int w = 1 << (m - r), wmin = (1 << r) - 1;
Matrix H_short;
while (res.size[0] < sz)
{
x = Code.FindWeight_simple(code_r.G, w);
H_short = new Matrix(n - k, n - w);
int c = 0; ind_f.Clear();
for (int j = 0; j < n; ++j)
{
if (x.data[j] == 0)
{
for (int i = 0; i < code_r.H.size[0]; ++i)
{
H_short.data[i][c] = code_r.H.data[i][j];
}
ind_f.Add(j);
++c;
}
}
MatrixFuncs.Gauss(H_short); //выделяем максимальную л.н. подсистему
Ind_set(H_short, ind_f, r, m, (long)n, ind_sets);
List <Vector> vecs = new List <Vector>();
for (int i = 0; i < wmin; ++i)
{
vecs.Add(new Vector(n));
for (int j = 0; j < w; j++)
{
vecs[i].data[ind_sets[i][j]] = 1;
}
}
for (int i = 0; i < wmin; ++i)
{
for (int j = 0; j < n; j++)
{
if (x.data[j] != 0)
{
vecs[i].data[j] = 1;
}
}
if (code_r.IsCodeWord(vecs[i]))
{
if (res.size[0] == 0 || MatrixFuncs.Gauss(res & vecs[i]) == res.size[0] + 1)
{
res &= vecs[i];
}
}
if (res.size[0] == sz)
{
return(new Code(res));
}
}
ind_f.Clear();
}
return(new Code(res));
}
//Gaussian elimination
public static int Gauss(Matrix A)
{
if (A == null || A.size[0] == 0)
{
return(0);
}
int k = A.size[0], n = A.size[1];
bool flag = true; int rank = 0;
for (int i = 0, j = 0; i < k && j < n; ++i, ++j)//c - для инф. окна
{
if (i == k - 1)
{
if (A.data[k - 1][j] != 0)
{
for (int ii = 0; ii < k - 1; ++ii)
{
if (A.data[ii][j] != 0)
{
for (int s = 0; s < n; ++s)
{
A.data[ii][s] = (A.data[ii][s] + A.data[k - 1][s]) & 1;
}
}
}
++rank;
break;
}
else
{
i--;
}
}
else
{
if (A.data[i][j] == 0)
{
flag = false;
for (int s = i + 1; s < k; ++s)
{
if (A.data[s][j] != 0)
{
flag = true;
MatrixFuncs.SwapRows(A, i, s);
break;
}
}
}
if (flag)
{
for (int s = 0; s < k; ++s)
{
if (s != i && A.data[s][j] != 0)
{
for (int q = 0; q < n; q++)
{
A.data[s][q] = (A.data[s][q] + A.data[i][q]) & 1;
}
}
}
++rank;
}
else
{
i--; flag = true;
}
}
}
//избавление от нулевых строк
for (int i = rank; i < k; ++i)
{
A -= rank;
}
return(rank);
}
public double AttackRM(out Matrix N1, out Matrix P1)
{
int k = Gp.size[0], n = Gp.size[1];
N1 = new Matrix(k, k); P1 = new Matrix(n, n);
Code code = new Code(Gp); Code Gp_reduced;
// Compute r, m
int r = -1, m = (int)Math.Log(n, 2), k1 = 0;
while (k1 < k)
{
++r;
k1 += Common.C(m, r);
}
RM rm = new RM(r, m);
Stopwatch t = new Stopwatch(); t.Start();
// Reduction
//2 * r >= m => reduction on dual code
if (2 * r < m || m - r == 1)
{
Gp_reduced = new Code(code.G);
}
else
{
Gp_reduced = new Code(code.H);
r = m - r - 1;
}
while (r > 1)
{
Gp_reduced = AttackFuncs.Reduction(Gp_reduced, r, m);
--r;
}
// Matrix P
Matrix Tmp; int idx = -1;
Vector e = new Vector(Enumerable.Repeat(1, n).ToList());
do
{
++idx;
Tmp = (new Matrix(Gp_reduced.G) - idx) & e;
}while (MatrixFuncs.Gauss(Tmp) < m + 1);
Tmp = Gp_reduced.G; Tmp -= idx; Matrix RM_1 = (new RM(1, m)).G -= 0;
IEnumerable <int> tmp1, tmp2;
Matrix P1_inv = new Matrix(n, n);
for (int j = 0; j < n; ++j)
{
tmp1 = Tmp.data.Select(x => x[j]);
for (int jj = 0; jj < n; ++jj)
{
tmp2 = RM_1.data.Select(x => x[jj]);
if (tmp1.SequenceEqual(tmp2))
{
P1.data[jj][j] = 1;
P1_inv.data[j][jj] = 1;
break;
}
}
}
// Matrix N
code.G = code.G * P1_inv;
N1 = MatrixFuncs.Transp(MatrixFuncs.SolveEq(MatrixFuncs.Transp(rm.G), MatrixFuncs.Transp(code.G)));
t.Stop();
return(t.ElapsedMilliseconds / 1000.00);
}
//Gaussian elimination with information window
public static int Gauss_E(Matrix A, out List <int> I, out List <int> J)
{
I = new List <int>(); J = new List <int>();
if (A == null || A.size[0] == 0)
{
return(0);
}
int k = A.size[0], n = A.size[1];
if (k <= n)
{
bool flag = true;
for (int i = 0, c = 0, j = 0; i < k && j < n; ++i, ++c, ++j)//c - для инф. окна
{
if (i == k - 1)
{
if (A.data[k - 1][j] != 0)
{
for (int ii = 0; ii < k - 1; ++ii)
{
if (A.data[ii][j] != 0)
{
for (int s = 0; s < n; ++s)
{
A.data[ii][s] = (A.data[ii][s] + A.data[k - 1][s]) & 1;
}
}
}
I.Add(j); ++j;
while (j < n)
{
J.Add(j); ++j;
}
break;
}
else
{
i--; J.Add(j);
}
}
else
{
if (A.data[i][j] == 0)
{
flag = false;
for (int s = i + 1; s < k; ++s)
{
if (A.data[s][j] != 0)
{
flag = true;
MatrixFuncs.SwapRows(A, i, s);
break;
}
}
}
if (flag)
{
for (int s = 0; s < k; ++s)
{
if (s != i && A.data[s][j] != 0)
{
for (int q = 0; q < n; q++)
{
A.data[s][q] = (A.data[s][q] + A.data[i][q]) & 1;
}
}
}
I.Add(j);
}
else
{
c--; i--; J.Add(j); flag = true;
}
}
}
//избавление от нулевых строк
for (int i = I.Count; i < A.size[0]; ++i)
{
A -= I.Count;
}
return(I.Count);
}
return(-1);
}
