Botan::PointGFp_Var_Point_Precompute Class Reference

#include <point_mul.h>

Public Member Functions
PointGFp	mul (const BigInt &k, RandomNumberGenerator &rng, const BigInt &group_order, std::vector< BigInt > &ws) const
	PointGFp_Var_Point_Precompute (const PointGFp &point, RandomNumberGenerator &rng, std::vector< BigInt > &ws)

Detailed Description

Definition at line 41 of file point_mul.h.

Constructor & Destructor Documentation

PointGFp_Var_Point_Precompute()

Botan::PointGFp_Var_Point_Precompute::PointGFp_Var_Point_Precompute	(	const PointGFp &	point,
		RandomNumberGenerator &	rng,
		std::vector< BigInt > &	ws
	)

Definition at line 201 of file point_mul.cpp.

                                                                                    :
   m_curve(point.get_curve()),
   m_p_words(m_curve.get_p().sig_words()),
   m_window_bits(4)
   {
   if(ws.size() < PointGFp::WORKSPACE_SIZE)
      ws.resize(PointGFp::WORKSPACE_SIZE);

   std::vector<PointGFp> U(static_cast<size_t>(1) << m_window_bits);
   U[0] = point.zero();
   U[1] = point;

   for(size_t i = 2; i < U.size(); i += 2)
      {
      U[i] = U[i/2].double_of(ws);
      U[i+1] = U[i].plus(point, ws);
      }

   // Hack to handle Blinded_Point_Multiply
   if(rng.is_seeded())
      {
      BigInt& mask = ws[0];
      BigInt& mask2 = ws[1];
      BigInt& mask3 = ws[2];
      BigInt& new_x = ws[3];
      BigInt& new_y = ws[4];
      BigInt& new_z = ws[5];
      secure_vector<word>& tmp = ws[6].get_word_vector();

      const CurveGFp& curve = U[0].get_curve();

      const size_t p_bits = curve.get_p().bits();

      // Skipping zero point since it can't be randomized
      for(size_t i = 1; i != U.size(); ++i)
         {
         mask.randomize(rng, p_bits - 1, false);
         // Easy way of ensuring mask != 0
         mask.set_bit(0);

         curve.sqr(mask2, mask, tmp);
         curve.mul(mask3, mask, mask2, tmp);

         curve.mul(new_x, U[i].get_x(), mask2, tmp);
         curve.mul(new_y, U[i].get_y(), mask3, tmp);
         curve.mul(new_z, U[i].get_z(), mask, tmp);

         U[i].swap_coords(new_x, new_y, new_z);
         }
      }

   m_T.resize(U.size() * 3 * m_p_words);

   word* p = &m_T[0];
   for(size_t i = 0; i != U.size(); ++i)
      {
      U[i].get_x().encode_words(p              , m_p_words);
      U[i].get_y().encode_words(p +   m_p_words, m_p_words);
      U[i].get_z().encode_words(p + 2*m_p_words, m_p_words);
      p += 3*m_p_words;
      }
   }

Member Function Documentation

mul()

PointGFp Botan::PointGFp_Var_Point_Precompute::mul	(	const BigInt &	k,
		RandomNumberGenerator &	rng,
		const BigInt &	group_order,
		std::vector< BigInt > &	ws
	)		const

Definition at line 266 of file point_mul.cpp.

References Botan::BigInt::bits(), BOTAN_DEBUG_ASSERT, Botan::clear_mem(), Botan::BigInt::get_substring(), Botan::CT::Mask< T >::is_equal(), Botan::BigInt::is_negative(), Botan::round_up(), and Botan::PointGFp::WORKSPACE_SIZE.

Referenced by Botan::EC_Group::blinded_var_point_multiply().

   {
   if(k.is_negative())
      throw Invalid_Argument("PointGFp_Var_Point_Precompute scalar must be positive");
   if(ws.size() < PointGFp::WORKSPACE_SIZE)
      ws.resize(PointGFp::WORKSPACE_SIZE);

   // Choose a small mask m and use k' = k + m*order (Coron's 1st countermeasure)
   const BigInt mask(rng, blinding_size(group_order), false);
   const BigInt scalar = k + group_order * mask;

   const size_t elem_size = 3*m_p_words;
   const size_t window_elems = (1ULL << m_window_bits);

   size_t windows = round_up(scalar.bits(), m_window_bits) / m_window_bits;
   PointGFp R(m_curve);
   secure_vector<word> e(elem_size);

   if(windows > 0)
      {
      windows--;

      const uint32_t w = scalar.get_substring(windows*m_window_bits, m_window_bits);

      clear_mem(e.data(), e.size());
      for(size_t i = 1; i != window_elems; ++i)
         {
         const auto wmask = CT::Mask<word>::is_equal(w, i);

         for(size_t j = 0; j != elem_size; ++j)
            {
            e[j] |= wmask.if_set_return(m_T[i * elem_size + j]);
            }
         }

      R.add(&e[0], m_p_words, &e[m_p_words], m_p_words, &e[2*m_p_words], m_p_words, ws);

      /*
      Randomize after adding the first nibble as before the addition R
      is zero, and we cannot effectively randomize the point
      representation of the zero point.
      */
      R.randomize_repr(rng, ws[0].get_word_vector());
      }

   while(windows)
      {
      R.mult2i(m_window_bits, ws);

      const uint32_t w = scalar.get_substring((windows-1)*m_window_bits, m_window_bits);

      clear_mem(e.data(), e.size());
      for(size_t i = 1; i != window_elems; ++i)
         {
         const auto wmask = CT::Mask<word>::is_equal(w, i);

         for(size_t j = 0; j != elem_size; ++j)
            {
            e[j] |= wmask.if_set_return(m_T[i * elem_size + j]);
            }
         }

      R.add(&e[0], m_p_words, &e[m_p_words], m_p_words, &e[2*m_p_words], m_p_words, ws);

      windows--;
      }

   BOTAN_DEBUG_ASSERT(R.on_the_curve());

   return R;
   }

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The documentation for this class was generated from the following files:

• src/lib/pubkey/ec_group/point_mul.h
• src/lib/pubkey/ec_group/point_mul.cpp