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/**
* (C) Copyright Projet SECRET, INRIA, Rocquencourt
* (C) Bhaskar Biswas and Nicolas Sendrier
*
* (C) 2014 cryptosource GmbH
* (C) 2014 Falko Strenzke fstrenzke@cryptosource.de
* (C) 2015 Jack Lloyd
*
* Botan is released under the Simplified BSD License (see license.txt)
*
*/
#include <botan/mceliece.h>
#include <botan/internal/mce_internal.h>
#include <botan/internal/code_based_util.h>
#include <botan/loadstor.h>
namespace Botan {
namespace {
struct binary_matrix
{
public:
binary_matrix(u32bit m_rown, u32bit m_coln);
void row_xor(u32bit a, u32bit b);
secure_vector<int> row_reduced_echelon_form();
/**
* return the coefficient out of F_2
*/
u32bit coef(u32bit i, u32bit j)
{
return (m_elem[(i) * m_rwdcnt + (j) / 32] >> (j % 32)) & 1;
};
void set_coef_to_one(u32bit i, u32bit j)
{
m_elem[(i) * m_rwdcnt + (j) / 32] |= (static_cast<u32bit>(1) << ((j) % 32)) ;
};
void toggle_coeff(u32bit i, u32bit j)
{
m_elem[(i) * m_rwdcnt + (j) / 32] ^= (static_cast<u32bit>(1) << ((j) % 32)) ;
}
void set_to_zero()
{
zeroise(m_elem);
}
//private:
u32bit m_rown; // number of rows.
u32bit m_coln; // number of columns.
u32bit m_rwdcnt; // number of words in a row
std::vector<u32bit> m_elem;
};
binary_matrix::binary_matrix (u32bit rown, u32bit coln)
{
m_coln = coln;
m_rown = rown;
m_rwdcnt = 1 + ((m_coln - 1) / 32);
m_elem = std::vector<u32bit>(m_rown * m_rwdcnt);
}
void binary_matrix::row_xor(u32bit a, u32bit b)
{
u32bit i;
for(i=0;i<m_rwdcnt;i++)
{
m_elem[a*m_rwdcnt+i]^=m_elem[b*m_rwdcnt+i];
}
}
//the matrix is reduced from LSB...(from right)
secure_vector<int> binary_matrix::row_reduced_echelon_form()
{
u32bit i, failcnt, findrow, max=m_coln - 1;
secure_vector<int> perm(m_coln);
for(i=0;i<m_coln;i++)
{
perm[i]=i;//initialize permutation.
}
failcnt = 0;
for(i=0;i<m_rown;i++,max--)
{
findrow=0;
for(u32bit j=i;j<m_rown;j++)
{
if(coef(j,max))
{
if (i!=j)//not needed as ith row is 0 and jth row is 1.
row_xor(i,j);//xor to the row.(swap)?
findrow=1;
break;
}//largest value found (end if)
}
if(!findrow)//if no row with a 1 found then swap last column and the column with no 1 down.
{
perm[m_coln - m_rown - 1 - failcnt] = max;
failcnt++;
if (!max)
{
//CSEC_FREE_MEM_CHK_SET_NULL(*p_perm);
//CSEC_THR_RETURN();
perm.resize(0);
}
i--;
}
else
{
perm[i+m_coln - m_rown] = max;
for(u32bit j=i+1;j<m_rown;j++)//fill the column downwards with 0's
{
if(coef(j,(max)))
{
row_xor(j,i);//check the arg. order.
}
}
for(int j=i-1;j>=0;j--)//fill the column with 0's upwards too.
{
if(coef(j,(max)))
{
row_xor(j,i);
}
}
}
}//end for(i)
return perm;
}
void randomize_support(std::vector<gf2m>& L, RandomNumberGenerator& rng)
{
for(u32bit i = 0; i != L.size(); ++i)
{
gf2m rnd = random_gf2m(rng);
// no rejection sampling, but for useful code-based parameters with n <= 13 this seem tolerable
std::swap(L[i], L[rnd % L.size()]);
}
}
std::unique_ptr<binary_matrix> generate_R(std::vector<gf2m> &L, polyn_gf2m* g, std::shared_ptr<GF2m_Field> sp_field, u32bit code_length, u32bit t )
{
//L- Support
//t- Number of errors
//n- Length of the Goppa code
//m- The extension degree of the GF
//g- The generator polynomial.
gf2m x,y;
u32bit i,j,k,r,n;
std::vector<int> Laux(code_length);
n=code_length;
r=t*sp_field->get_extension_degree();
binary_matrix H(r, n) ;
for(i=0;i< n;i++)
{
x = g->eval(lex_to_gray(L[i]));//evaluate the polynomial at the point L[i].
x = sp_field->gf_inv(x);
y = x;
for(j=0;j<t;j++)
{
for(k=0;k<sp_field->get_extension_degree();k++)
{
if(y & (1<<k))
{
//the co-eff. are set in 2^0,...,2^11 ; 2^0,...,2^11 format along the rows/cols?
H.set_coef_to_one(j*sp_field->get_extension_degree()+ k,i);
}
}
y = sp_field->gf_mul(y,lex_to_gray(L[i]));
}
}//The H matrix is fed.
secure_vector<int> perm = H.row_reduced_echelon_form();
if (perm.size() == 0)
{
// result still is NULL
throw Invalid_State("could not bring matrix in row reduced echelon form");
}
std::unique_ptr<binary_matrix> result(new binary_matrix(n-r,r)) ;
for (i = 0; i < (*result).m_rown; ++i)
{
for (j = 0; j < (*result).m_coln; ++j)
{
if (H.coef(j,perm[i]))
{
result->toggle_coeff(i,j);
}
}
}
for (i = 0; i < code_length; ++i)
{
Laux[i] = L[perm[i]];
}
for (i = 0; i < code_length; ++i)
{
L[i] = Laux[i];
}
return result;
}
}
McEliece_PrivateKey generate_mceliece_key( RandomNumberGenerator & rng, u32bit ext_deg, u32bit code_length, u32bit t)
{
u32bit i, j, k, l;
std::unique_ptr<binary_matrix> R;
u32bit codimension = t * ext_deg;
if(code_length <= codimension)
{
throw Invalid_Argument("invalid McEliece parameters");
}
std::shared_ptr<GF2m_Field> sp_field ( new GF2m_Field(ext_deg ));
//pick the support.........
std::vector<gf2m> L(code_length);
for(i=0;i<code_length;i++)
{
L[i]=i;
}
randomize_support(L, rng);
polyn_gf2m g(sp_field); // create as zero
bool success = false;
do
{
// create a random irreducible polynomial
g = polyn_gf2m (t, rng, sp_field);
try{
R = generate_R(L,&g, sp_field, code_length, t);
success = true;
}
catch(const Invalid_State &)
{
}
} while (!success);
std::vector<polyn_gf2m> sqrtmod = polyn_gf2m::sqrt_mod_init( g);
std::vector<polyn_gf2m> F = syndrome_init(g, L, code_length);
// Each F[i] is the (precomputed) syndrome of the error vector with
// a single '1' in i-th position.
// We do not store the F[i] as polynomials of degree t , but
// as binary vectors of length ext_deg * t (this will
// speed up the syndrome computation)
//
//
std::vector<u32bit> H(bit_size_to_32bit_size(codimension) * code_length );
u32bit* sk = H.data();
for (i = 0; i < code_length; ++i)
{
for (l = 0; l < t; ++l)
{
k = (l * ext_deg) / 32;
j = (l * ext_deg) % 32;
sk[k] ^= static_cast<u32bit>(F[i].get_coef(l)) << j;
if (j + ext_deg > 32)
{
sk[k + 1] ^= F[i].get_coef( l) >> (32 - j);
}
}
sk += bit_size_to_32bit_size(codimension);
}
// We need the support L for decoding (decryption). In fact the
// inverse is needed
std::vector<gf2m> Linv(code_length) ;
for (i = 0; i < code_length; ++i)
{
Linv[L[i]] = i;
}
std::vector<byte> pubmat (R->m_elem.size() * 4);
for(i = 0; i < R->m_elem.size(); i++)
{
store_le(R->m_elem[i], &pubmat[i*4]);
}
return McEliece_PrivateKey(g, H, sqrtmod, Linv, pubmat);
}
}
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