mirror of
https://github.com/henrydcase/pqc.git
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629 lines
20 KiB
C
629 lines
20 KiB
C
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/**
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* @file fft.c
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* Implementation of the additive FFT and its transpose.
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* This implementation is based on the paper from Gao and Mateer: <br>
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* Shuhong Gao and Todd Mateer, Additive Fast Fourier Transforms over Finite Fields,
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* IEEE Transactions on Information Theory 56 (2010), 6265--6272.
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* http://www.math.clemson.edu/~sgao/papers/GM10.pdf <br>
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* and includes improvements proposed by Bernstein, Chou and Schwabe here:
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* https://binary.cr.yp.to/mcbits-20130616.pdf
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*/
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#include "fft.h"
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#include "gf.h"
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#include "parameters.h"
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#include <stdint.h>
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#include <string.h>
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static void compute_fft_betas(uint16_t *betas);
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static void compute_subset_sums(uint16_t *subset_sums, const uint16_t *set, size_t set_size);
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static void radix_t(uint16_t *f, const uint16_t *f0, const uint16_t *f1, uint32_t m_f);
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static void fft_t_rec(uint16_t *f, const uint16_t *w, size_t f_coeffs, uint8_t m, uint32_t m_f, const uint16_t *betas);
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static void radix(uint16_t *f0, uint16_t *f1, const uint16_t *f, uint32_t m_f);
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static void fft_rec(uint16_t *w, uint16_t *f, size_t f_coeffs, uint8_t m, uint32_t m_f, const uint16_t *betas);
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/**
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* @brief Computes the basis of betas (omitting 1) used in the additive FFT and its transpose
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*
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* @param[out] betas Array of size PARAM_M-1
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*/
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static void compute_fft_betas(uint16_t *betas) {
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for (size_t i = 0; i < PARAM_M - 1; ++i) {
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betas[i] = 1 << (PARAM_M - 1 - i);
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}
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}
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/**
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* @brief Computes the subset sums of the given set
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*
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* The array subset_sums is such that its ith element is
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* the subset sum of the set elements given by the binary form of i.
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*
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* @param[out] subset_sums Array of size 2^set_size receiving the subset sums
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* @param[in] set Array of set_size elements
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* @param[in] set_size Size of the array set
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*/
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static void compute_subset_sums(uint16_t *subset_sums, const uint16_t *set, size_t set_size) {
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subset_sums[0] = 0;
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for (size_t i = 0; i < set_size; ++i) {
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for (size_t j = 0; j < (((size_t)1) << i); ++j) {
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subset_sums[(((size_t)1) << i) + j] = set[i] ^ subset_sums[j];
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}
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}
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}
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/**
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* @brief Transpose of the linear radix conversion
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*
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* This is a direct transposition of the radix function
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* implemented following the process of transposing a linear function as exposed by Bernstein, Chou and Schwabe here:
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* https://binary.cr.yp.to/mcbits-20130616.pdf
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*
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* @param[out] f Array of size a power of 2
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* @param[in] f0 Array half the size of f
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* @param[in] f1 Array half the size of f
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* @param[in] m_f 2^{m_f} is the smallest power of 2 greater or equal to the number of coefficients of f
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*/
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static void radix_t(uint16_t *f, const uint16_t *f0, const uint16_t *f1, uint32_t m_f) {
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switch (m_f) {
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case 4:
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f[0] = f0[0];
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f[1] = f1[0];
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f[2] = f0[1] ^ f1[0];
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f[3] = f[2] ^ f1[1];
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f[4] = f[2] ^ f0[2];
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f[5] = f[3] ^ f1[2];
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f[6] = f[4] ^ f0[3] ^ f1[2];
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f[7] = f[3] ^ f0[3] ^ f1[3];
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f[8] = f[4] ^ f0[4];
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f[9] = f[5] ^ f1[4];
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f[10] = f[6] ^ f0[5] ^ f1[4];
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f[11] = f[7] ^ f0[5] ^ f1[4] ^ f1[5];
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f[12] = f[8] ^ f0[5] ^ f0[6] ^ f1[4];
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f[13] = f[7] ^ f[9] ^ f[11] ^ f1[6];
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f[14] = f[6] ^ f0[6] ^ f0[7] ^ f1[6];
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f[15] = f[7] ^ f0[7] ^ f1[7];
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return;
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case 3:
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f[0] = f0[0];
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f[1] = f1[0];
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f[2] = f0[1] ^ f1[0];
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f[3] = f[2] ^ f1[1];
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f[4] = f[2] ^ f0[2];
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f[5] = f[3] ^ f1[2];
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f[6] = f[4] ^ f0[3] ^ f1[2];
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f[7] = f[3] ^ f0[3] ^ f1[3];
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return;
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case 2:
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f[0] = f0[0];
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f[1] = f1[0];
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f[2] = f0[1] ^ f1[0];
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f[3] = f[2] ^ f1[1];
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return;
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case 1:
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f[0] = f0[0];
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f[1] = f1[0];
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return;
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default:
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;
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size_t n = ((size_t)1) << (m_f - 2);
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uint16_t Q0[1 << (PARAM_FFT_T - 2)] = {0};
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uint16_t Q1[1 << (PARAM_FFT_T - 2)] = {0};
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uint16_t R0[1 << (PARAM_FFT_T - 2)] = {0};
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uint16_t R1[1 << (PARAM_FFT_T - 2)] = {0};
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uint16_t Q[1 << 2 * (PARAM_FFT_T - 2)] = {0};
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uint16_t R[1 << 2 * (PARAM_FFT_T - 2)] = {0};
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memcpy(Q0, f0 + n, 2 * n);
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memcpy(Q1, f1 + n, 2 * n);
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memcpy(R0, f0, 2 * n);
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memcpy(R1, f1, 2 * n);
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radix_t (Q, Q0, Q1, m_f - 1);
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radix_t (R, R0, R1, m_f - 1);
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memcpy(f, R, 4 * n);
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memcpy(f + 2 * n, R + n, 2 * n);
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memcpy(f + 3 * n, Q + n, 2 * n);
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for (size_t i = 0; i < n; ++i) {
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f[2 * n + i] ^= Q[i];
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f[3 * n + i] ^= f[2 * n + i];
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}
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}
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}
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/**
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* @brief Recursively computes syndromes of family w
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*
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* This function is a subroutine of the function fft_t
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*
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* @param[out] f Array receiving the syndromes
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* @param[in] w Array storing the family
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* @param[in] f_coeffs Length of syndromes vector
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* @param[in] m 2^m is the smallest power of 2 greater or equal to the length of family w
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* @param[in] m_f 2^{m_f} is the smallest power of 2 greater or equal to the length of f
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* @param[in] betas FFT constants
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*/
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static void fft_t_rec(uint16_t *f, const uint16_t *w, size_t f_coeffs,
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uint8_t m, uint32_t m_f, const uint16_t *betas) {
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size_t k = ((size_t)1) << (m - 1);
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uint16_t gammas[PARAM_M - 2] = {0};
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uint16_t deltas[PARAM_M - 2] = {0};
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uint16_t gammas_sums[1 << (PARAM_M - 1)];
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uint16_t u[1 << (PARAM_M - 2)] = {0};
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uint16_t f0[1 << (PARAM_FFT_T - 2)] = {0};
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uint16_t f1[1 << (PARAM_FFT_T - 2)] = {0};
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uint16_t betas_sums[1 << (PARAM_M - 1)] = {0};
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// Step 1
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if (m_f == 1) {
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for (size_t i = 0; i < (((size_t)1) << m); ++i) {
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f[0] ^= w[i];
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}
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for (size_t j = 0; j < m; ++j) {
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for (size_t ki = 0; ki < (((size_t)1) << j); ++ki) {
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size_t index = (((size_t)1) << j) + ki;
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betas_sums[index] = betas_sums[ki] ^ betas[j];
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f[1] ^= PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(betas_sums[index], w[index]);
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}
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}
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return;
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}
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// Compute gammas and deltas
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for (uint8_t i = 0; i < m - 1; ++i) {
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gammas[i] = PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(betas[i], PQCLEAN_HQC2561CCA2_LEAKTIME_gf_inverse(betas[m - 1]));
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deltas[i] = PQCLEAN_HQC2561CCA2_LEAKTIME_gf_square(gammas[i]) ^ gammas[i];
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}
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// Compute gammas subset sums
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compute_subset_sums(gammas_sums, gammas, m - 1);
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/* Step 6: Compute u and v from w (aka w)
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* w[i] = u[i] + G[i].v[i]
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* w[k+i] = w[i] + v[i] = u[i] + (G[i]+1).v[i]
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* Transpose:
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* u[i] = w[i] + w[k+i]
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* v[i] = G[i].w[i] + (G[i]+1).w[k+i] = G[i].u[i] + w[k+i] */
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if (f_coeffs <= 3) { // 3-coefficient polynomial f case
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// Step 5: Compute f0 from u and f1 from v
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f1[1] = 0;
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u[0] = w[0] ^ w[k];
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f1[0] = w[k];
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for (size_t i = 1; i < k; ++i) {
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u[i] = w[i] ^ w[k + i];
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f1[0] ^= PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(gammas_sums[i], u[i]) ^ w[k + i];
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}
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fft_t_rec(f0, u, (f_coeffs + 1) / 2, m - 1, m_f - 1, deltas);
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} else {
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uint16_t v[1 << (PARAM_M - 2)] = {0};
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u[0] = w[0] ^ w[k];
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v[0] = w[k];
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for (size_t i = 1; i < k; ++i) {
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u[i] = w[i] ^ w[k + i];
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v[i] = PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(gammas_sums[i], u[i]) ^ w[k + i];
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}
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// Step 5: Compute f0 from u and f1 from v
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fft_t_rec(f0, u, (f_coeffs + 1) / 2, m - 1, m_f - 1, deltas);
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fft_t_rec(f1, v, f_coeffs / 2, m - 1, m_f - 1, deltas);
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}
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// Step 3: Compute g from g0 and g1
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radix_t(f, f0, f1, m_f);
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// Step 2: compute f from g
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if (betas[m - 1] != 1) {
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uint16_t beta_m_pow = 1;
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for (size_t i = 1; i < (((size_t)1) << m_f); ++i) {
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beta_m_pow = PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(beta_m_pow, betas[m - 1]);
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f[i] = PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(beta_m_pow, f[i]);
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}
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}
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}
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/**
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* @brief Computes the syndromes f of the family w
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*
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* Since the syndromes linear map is the transpose of multipoint evaluation,
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* it uses exactly the same constants, either hardcoded or precomputed by compute_fft_lut(...). <br>
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* This follows directives from Bernstein, Chou and Schwabe given here:
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* https://binary.cr.yp.to/mcbits-20130616.pdf
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*
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* @param[out] f Array of size 2*(PARAM_FFT_T) elements receiving the syndromes
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* @param[in] w Array of PARAM_GF_MUL_ORDER+1 elements
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* @param[in] f_coeffs Length of syndromes vector f
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*/
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void PQCLEAN_HQC2561CCA2_LEAKTIME_fft_t(uint16_t *f, const uint16_t *w, size_t f_coeffs) {
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// Transposed from Gao and Mateer algorithm
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uint16_t betas[PARAM_M - 1];
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uint16_t betas_sums[1 << (PARAM_M - 1)];
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size_t k = 1 << (PARAM_M - 1);
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uint16_t u[1 << (PARAM_M - 1)] = {0};
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uint16_t v[1 << (PARAM_M - 1)] = {0};
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uint16_t deltas[PARAM_M - 1];
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uint16_t f0[1 << (PARAM_FFT_T - 1)];
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uint16_t f1[1 << (PARAM_FFT_T - 1)];
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compute_fft_betas(betas);
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compute_subset_sums(betas_sums, betas, PARAM_M - 1);
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/* Step 6: Compute u and v from w (aka w)
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*
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* We had:
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* w[i] = u[i] + G[i].v[i]
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* w[k+i] = w[i] + v[i] = u[i] + (G[i]+1).v[i]
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* Transpose:
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* u[i] = w[i] + w[k+i]
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* v[i] = G[i].w[i] + (G[i]+1).w[k+i] = G[i].u[i] + w[k+i] */
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u[0] = w[0] ^ w[k];
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v[0] = w[k];
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for (size_t i = 1; i < k; ++i) {
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u[i] = w[i] ^ w[k + i];
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v[i] = PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(betas_sums[i], u[i]) ^ w[k + i];
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}
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// Compute deltas
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for (size_t i = 0; i < PARAM_M - 1; ++i) {
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deltas[i] = PQCLEAN_HQC2561CCA2_LEAKTIME_gf_square(betas[i]) ^ betas[i];
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}
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// Step 5: Compute f0 from u and f1 from v
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fft_t_rec(f0, u, (f_coeffs + 1) / 2, PARAM_M - 1, PARAM_FFT_T - 1, deltas);
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fft_t_rec(f1, v, f_coeffs / 2, PARAM_M - 1, PARAM_FFT_T - 1, deltas);
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// Step 3: Compute g from g0 and g1
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radix_t(f, f0, f1, PARAM_FFT_T);
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// Step 2: beta_m = 1 so f = g
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}
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/**
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* @brief Computes the radix conversion of a polynomial f in GF(2^m)[x]
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*
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* Computes f0 and f1 such that f(x) = f0(x^2-x) + x.f1(x^2-x)
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* as proposed by Bernstein, Chou and Schwabe:
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* https://binary.cr.yp.to/mcbits-20130616.pdf
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*
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* @param[out] f0 Array half the size of f
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* @param[out] f1 Array half the size of f
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* @param[in] f Array of size a power of 2
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* @param[in] m_f 2^{m_f} is the smallest power of 2 greater or equal to the number of coefficients of f
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*/
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static void radix(uint16_t *f0, uint16_t *f1, const uint16_t *f, uint32_t m_f) {
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switch (m_f) {
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case 4:
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f0[4] = f[8] ^ f[12];
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f0[6] = f[12] ^ f[14];
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f0[7] = f[14] ^ f[15];
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f1[5] = f[11] ^ f[13];
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f1[6] = f[13] ^ f[14];
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f1[7] = f[15];
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f0[5] = f[10] ^ f[12] ^ f1[5];
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f1[4] = f[9] ^ f[13] ^ f0[5];
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f0[0] = f[0];
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f1[3] = f[7] ^ f[11] ^ f[15];
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f0[3] = f[6] ^ f[10] ^ f[14] ^ f1[3];
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f0[2] = f[4] ^ f0[4] ^ f0[3] ^ f1[3];
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f1[1] = f[3] ^ f[5] ^ f[9] ^ f[13] ^ f1[3];
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f1[2] = f[3] ^ f1[1] ^ f0[3];
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f0[1] = f[2] ^ f0[2] ^ f1[1];
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f1[0] = f[1] ^ f0[1];
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return;
|
||
|
|
||
|
case 3:
|
||
|
f0[0] = f[0];
|
||
|
f0[2] = f[4] ^ f[6];
|
||
|
f0[3] = f[6] ^ f[7];
|
||
|
f1[1] = f[3] ^ f[5] ^ f[7];
|
||
|
f1[2] = f[5] ^ f[6];
|
||
|
f1[3] = f[7];
|
||
|
f0[1] = f[2] ^ f0[2] ^ f1[1];
|
||
|
f1[0] = f[1] ^ f0[1];
|
||
|
return;
|
||
|
|
||
|
case 2:
|
||
|
f0[0] = f[0];
|
||
|
f0[1] = f[2] ^ f[3];
|
||
|
f1[0] = f[1] ^ f0[1];
|
||
|
f1[1] = f[3];
|
||
|
return;
|
||
|
|
||
|
case 1:
|
||
|
f0[0] = f[0];
|
||
|
f1[0] = f[1];
|
||
|
return;
|
||
|
|
||
|
default:
|
||
|
;
|
||
|
size_t n = ((size_t)1) << (m_f - 2);
|
||
|
|
||
|
uint16_t Q[2 * (1 << (PARAM_FFT - 2))];
|
||
|
uint16_t R[2 * (1 << (PARAM_FFT - 2))];
|
||
|
|
||
|
uint16_t Q0[1 << (PARAM_FFT - 2)];
|
||
|
uint16_t Q1[1 << (PARAM_FFT - 2)];
|
||
|
uint16_t R0[1 << (PARAM_FFT - 2)];
|
||
|
uint16_t R1[1 << (PARAM_FFT - 2)];
|
||
|
|
||
|
memcpy(Q, f + 3 * n, 2 * n);
|
||
|
memcpy(Q + n, f + 3 * n, 2 * n);
|
||
|
memcpy(R, f, 4 * n);
|
||
|
|
||
|
for (size_t i = 0; i < n; ++i) {
|
||
|
Q[i] ^= f[2 * n + i];
|
||
|
R[n + i] ^= Q[i];
|
||
|
}
|
||
|
|
||
|
radix(Q0, Q1, Q, m_f - 1);
|
||
|
radix(R0, R1, R, m_f - 1);
|
||
|
|
||
|
memcpy(f0, R0, 2 * n);
|
||
|
memcpy(f0 + n, Q0, 2 * n);
|
||
|
memcpy(f1, R1, 2 * n);
|
||
|
memcpy(f1 + n, Q1, 2 * n);
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
|
||
|
/**
|
||
|
* @brief Evaluates f at all subset sums of a given set
|
||
|
*
|
||
|
* This function is a subroutine of the function fft.
|
||
|
*
|
||
|
* @param[out] w Array
|
||
|
* @param[in] f Array
|
||
|
* @param[in] f_coeffs Number of coefficients of f
|
||
|
* @param[in] m Number of betas
|
||
|
* @param[in] m_f Number of coefficients of f (one more than its degree)
|
||
|
* @param[in] betas FFT constants
|
||
|
*/
|
||
|
static void fft_rec(uint16_t *w, uint16_t *f, size_t f_coeffs,
|
||
|
uint8_t m, uint32_t m_f, const uint16_t *betas) {
|
||
|
|
||
|
uint16_t f0[1 << (PARAM_FFT - 2)] = {0};
|
||
|
uint16_t f1[1 << (PARAM_FFT - 2)] = {0};
|
||
|
uint16_t gammas[PARAM_M - 2] = {0};
|
||
|
uint16_t deltas[PARAM_M - 2] = {0};
|
||
|
size_t k = ((size_t)1) << (m - 1);
|
||
|
uint16_t gammas_sums[1 << (PARAM_M - 2)] = {0};
|
||
|
uint16_t u[1 << (PARAM_M - 2)] = {0};
|
||
|
uint16_t v[1 << (PARAM_M - 2)] = {0};
|
||
|
|
||
|
// Step 1
|
||
|
if (m_f == 1) {
|
||
|
uint16_t tmp[PARAM_M - (PARAM_FFT - 1)];
|
||
|
for (size_t i = 0; i < m; ++i) {
|
||
|
tmp[i] = PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(betas[i], f[1]);
|
||
|
}
|
||
|
|
||
|
w[0] = f[0];
|
||
|
for (size_t j = 0; j < m; ++j) {
|
||
|
for (size_t ki = 0; ki < (((size_t)1) << j); ++ki) {
|
||
|
w[(((size_t)1) << j) + ki] = w[ki] ^ tmp[j];
|
||
|
}
|
||
|
}
|
||
|
|
||
|
return;
|
||
|
}
|
||
|
|
||
|
// Step 2: compute g
|
||
|
if (betas[m - 1] != 1) {
|
||
|
uint16_t beta_m_pow = 1;
|
||
|
for (size_t i = 1; i < (((size_t)1) << m_f); ++i) {
|
||
|
beta_m_pow = PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(beta_m_pow, betas[m - 1]);
|
||
|
f[i] = PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(beta_m_pow, f[i]);
|
||
|
}
|
||
|
}
|
||
|
|
||
|
// Step 3
|
||
|
radix(f0, f1, f, m_f);
|
||
|
|
||
|
// Step 4: compute gammas and deltas
|
||
|
for (uint8_t i = 0; i < m - 1; ++i) {
|
||
|
gammas[i] = PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(betas[i], PQCLEAN_HQC2561CCA2_LEAKTIME_gf_inverse(betas[m - 1]));
|
||
|
deltas[i] = PQCLEAN_HQC2561CCA2_LEAKTIME_gf_square(gammas[i]) ^ gammas[i];
|
||
|
}
|
||
|
|
||
|
// Compute gammas sums
|
||
|
compute_subset_sums(gammas_sums, gammas, m - 1);
|
||
|
|
||
|
// Step 5
|
||
|
fft_rec(u, f0, (f_coeffs + 1) / 2, m - 1, m_f - 1, deltas);
|
||
|
|
||
|
if (f_coeffs <= 3) { // 3-coefficient polynomial f case: f1 is constant
|
||
|
w[0] = u[0];
|
||
|
w[k] = u[0] ^ f1[0];
|
||
|
for (size_t i = 1; i < k; ++i) {
|
||
|
w[i] = u[i] ^ PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(gammas_sums[i], f1[0]);
|
||
|
w[k + i] = w[i] ^ f1[0];
|
||
|
}
|
||
|
} else {
|
||
|
fft_rec(v, f1, f_coeffs / 2, m - 1, m_f - 1, deltas);
|
||
|
|
||
|
// Step 6
|
||
|
memcpy(w + k, v, 2 * k);
|
||
|
w[0] = u[0];
|
||
|
w[k] ^= u[0];
|
||
|
for (size_t i = 1; i < k; ++i) {
|
||
|
w[i] = u[i] ^ PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(gammas_sums[i], v[i]);
|
||
|
w[k + i] ^= w[i];
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
|
||
|
/**
|
||
|
* @brief Evaluates f on all fields elements using an additive FFT algorithm
|
||
|
*
|
||
|
* f_coeffs is the number of coefficients of f (one less than its degree). <br>
|
||
|
* The FFT proceeds recursively to evaluate f at all subset sums of a basis B. <br>
|
||
|
* This implementation is based on the paper from Gao and Mateer: <br>
|
||
|
* Shuhong Gao and Todd Mateer, Additive Fast Fourier Transforms over Finite Fields,
|
||
|
* IEEE Transactions on Information Theory 56 (2010), 6265--6272.
|
||
|
* http://www.math.clemson.edu/~sgao/papers/GM10.pdf <br>
|
||
|
* and includes improvements proposed by Bernstein, Chou and Schwabe here:
|
||
|
* https://binary.cr.yp.to/mcbits-20130616.pdf <br>
|
||
|
* Constants betas, gammas and deltas involved in the algorithm are either hardcoded or precomputed
|
||
|
* by the subroutine compute_fft_lut(...). <br>
|
||
|
* Note that on this first call (as opposed to the recursive calls to fft_rec), gammas are equal to betas,
|
||
|
* meaning the first gammas subset sums are actually the subset sums of betas (except 1). <br>
|
||
|
* Also note that f is altered during computation (twisted at each level).
|
||
|
*
|
||
|
* @param[out] w Array
|
||
|
* @param[in] f Array of 2^PARAM_FFT elements
|
||
|
* @param[in] f_coeffs Number coefficients of f (i.e. deg(f)+1)
|
||
|
*/
|
||
|
void PQCLEAN_HQC2561CCA2_LEAKTIME_fft(uint16_t *w, const uint16_t *f, size_t f_coeffs) {
|
||
|
uint16_t betas[PARAM_M - 1] = {0};
|
||
|
uint16_t betas_sums[1 << (PARAM_M - 1)] = {0};
|
||
|
uint16_t f0[1 << (PARAM_FFT - 1)] = {0};
|
||
|
uint16_t f1[1 << (PARAM_FFT - 1)] = {0};
|
||
|
uint16_t deltas[PARAM_M - 1];
|
||
|
size_t k = 1 << (PARAM_M - 1);
|
||
|
uint16_t u[1 << (PARAM_M - 1)] = {0};
|
||
|
uint16_t v[1 << (PARAM_M - 1)] = {0};
|
||
|
|
||
|
// Follows Gao and Mateer algorithm
|
||
|
compute_fft_betas(betas);
|
||
|
|
||
|
// Step 1: PARAM_FFT > 1, nothing to do
|
||
|
|
||
|
// Compute gammas sums
|
||
|
compute_subset_sums(betas_sums, betas, PARAM_M - 1);
|
||
|
|
||
|
// Step 2: beta_m = 1, nothing to do
|
||
|
|
||
|
// Step 3
|
||
|
radix(f0, f1, f, PARAM_FFT);
|
||
|
|
||
|
// Step 4: Compute deltas
|
||
|
for (size_t i = 0; i < PARAM_M - 1; ++i) {
|
||
|
deltas[i] = PQCLEAN_HQC2561CCA2_LEAKTIME_gf_square(betas[i]) ^ betas[i];
|
||
|
}
|
||
|
|
||
|
// Step 5
|
||
|
fft_rec(u, f0, (f_coeffs + 1) / 2, PARAM_M - 1, PARAM_FFT - 1, deltas);
|
||
|
fft_rec(v, f1, f_coeffs / 2, PARAM_M - 1, PARAM_FFT - 1, deltas);
|
||
|
|
||
|
// Step 6, 7 and error polynomial computation
|
||
|
memcpy(w + k, v, 2 * k);
|
||
|
|
||
|
// Check if 0 is root
|
||
|
w[0] = u[0];
|
||
|
|
||
|
// Check if 1 is root
|
||
|
w[k] ^= u[0];
|
||
|
|
||
|
// Find other roots
|
||
|
for (size_t i = 1; i < k; ++i) {
|
||
|
w[i] = u[i] ^ PQCLEAN_HQC2561CCA2_LEAKTIME_gf_mul(betas_sums[i], v[i]);
|
||
|
w[k + i] ^= w[i];
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
|
||
|
/**
|
||
|
* @brief Arranges the received word vector in a form w such that applying the additive FFT transpose to w yields the BCH syndromes of the received word vector.
|
||
|
*
|
||
|
* Since the received word vector gives coefficients of the primitive element alpha, we twist accordingly. <br>
|
||
|
* Furthermore, the additive FFT transpose needs elements indexed by their decomposition on the chosen basis,
|
||
|
* so we apply the adequate permutation.
|
||
|
*
|
||
|
* @param[out] w Array of size 2^PARAM_M
|
||
|
* @param[in] vector Array of size VEC_N1_SIZE_BYTES
|
||
|
*/
|
||
|
void PQCLEAN_HQC2561CCA2_LEAKTIME_fft_t_preprocess_bch_codeword(uint16_t *w, const uint8_t *vector) {
|
||
|
uint16_t r[1 << PARAM_M];
|
||
|
uint16_t gammas[PARAM_M - 1];
|
||
|
uint16_t gammas_sums[1 << (PARAM_M - 1)];
|
||
|
size_t k = 1 << (PARAM_M - 1);
|
||
|
|
||
|
// Unpack the received word vector into array r
|
||
|
size_t i;
|
||
|
for (i = 0; i < VEC_N1_SIZE_BYTES - (PARAM_N1 % 8 != 0); ++i) {
|
||
|
for (size_t j = 0; j < 8; ++j) {
|
||
|
r[8 * i + j] = (vector[i] >> j) & 1;
|
||
|
}
|
||
|
}
|
||
|
|
||
|
// Last byte
|
||
|
for (size_t j = 0; j < PARAM_N1 % 8; ++j) {
|
||
|
r[8 * i + j] = (vector[i] >> j) & 1;
|
||
|
}
|
||
|
|
||
|
// Complete r with zeros
|
||
|
memset(r + PARAM_N1, 0, 2 * ((1 << PARAM_M) - PARAM_N1));
|
||
|
|
||
|
compute_fft_betas(gammas);
|
||
|
compute_subset_sums(gammas_sums, gammas, PARAM_M - 1);
|
||
|
|
||
|
// Twist and permute r adequately to obtain w
|
||
|
w[0] = 0;
|
||
|
w[k] = -r[0] & 1;
|
||
|
for (i = 1; i < k; ++i) {
|
||
|
w[i] = -r[PQCLEAN_HQC2561CCA2_LEAKTIME_gf_log(gammas_sums[i])] & gammas_sums[i];
|
||
|
w[k + i] = -r[PQCLEAN_HQC2561CCA2_LEAKTIME_gf_log(gammas_sums[i] ^ 1)] & (gammas_sums[i] ^ 1);
|
||
|
}
|
||
|
}
|
||
|
|
||
|
|
||
|
|
||
|
/**
|
||
|
* @brief Retrieves the error polynomial error from the evaluations w of the ELP (Error Locator Polynomial) on all field elements.
|
||
|
*
|
||
|
* @param[out] error Array of size VEC_N1_SIZE_BYTES
|
||
|
* @param[in] w Array of size 2^PARAM_M
|
||
|
*/
|
||
|
void PQCLEAN_HQC2561CCA2_LEAKTIME_fft_retrieve_bch_error_poly(uint8_t *error, const uint16_t *w) {
|
||
|
uint16_t gammas[PARAM_M - 1];
|
||
|
uint16_t gammas_sums[1 << (PARAM_M - 1)];
|
||
|
size_t k = 1 << (PARAM_M - 1);
|
||
|
size_t index = PARAM_GF_MUL_ORDER;
|
||
|
|
||
|
compute_fft_betas(gammas);
|
||
|
compute_subset_sums(gammas_sums, gammas, PARAM_M - 1);
|
||
|
|
||
|
error[0] ^= 1 ^ ((uint16_t) - w[0] >> 15);
|
||
|
uint8_t bit = 1 ^ ((uint16_t) - w[k] >> 15);
|
||
|
error[index / 8] ^= bit << (index % 8);
|
||
|
|
||
|
for (size_t i = 1; i < k; ++i) {
|
||
|
index = PARAM_GF_MUL_ORDER - PQCLEAN_HQC2561CCA2_LEAKTIME_gf_log(gammas_sums[i]);
|
||
|
bit = 1 ^ ((uint16_t) - w[i] >> 15);
|
||
|
error[index / 8] ^= bit << (index % 8);
|
||
|
|
||
|
index = PARAM_GF_MUL_ORDER - PQCLEAN_HQC2561CCA2_LEAKTIME_gf_log(gammas_sums[i] ^ 1);
|
||
|
bit = 1 ^ ((uint16_t) - w[k + i] >> 15);
|
||
|
error[index / 8] ^= bit << (index % 8);
|
||
|
}
|
||
|
}
|