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293 lines
9.7 KiB
C
293 lines
9.7 KiB
C
/*
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* Falcon signature generation.
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*
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* ==========================(LICENSE BEGIN)============================
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*
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* Copyright (c) 2017-2019 Falcon Project
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*
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* Permission is hereby granted, free of charge, to any person obtaining
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* a copy of this software and associated documentation files (the
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* "Software"), to deal in the Software without restriction, including
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* without limitation the rights to use, copy, modify, merge, publish,
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* distribute, sublicense, and/or sell copies of the Software, and to
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* permit persons to whom the Software is furnished to do so, subject to
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* the following conditions:
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*
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* The above copyright notice and this permission notice shall be
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* included in all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
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* IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
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* CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
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* TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
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* SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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*
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* ===========================(LICENSE END)=============================
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*
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* @author Thomas Pornin <[email protected]>
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*/
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#include "inner.h"
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#include <arm_neon.h>
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/*
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* Sample an integer value along a half-gaussian distribution centered
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* on zero and standard deviation 1.8205, with a precision of 72 bits.
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*/
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int
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PQCLEAN_FALCON512_AARCH64_gaussian0_sampler(prng *p) {
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static const uint32_t dist[] = {
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10745844u, 3068844u, 3741698u,
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5559083u, 1580863u, 8248194u,
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2260429u, 13669192u, 2736639u,
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708981u, 4421575u, 10046180u,
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169348u, 7122675u, 4136815u,
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30538u, 13063405u, 7650655u,
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4132u, 14505003u, 7826148u,
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417u, 16768101u, 11363290u,
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31u, 8444042u, 8086568u,
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1u, 12844466u, 265321u,
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0u, 1232676u, 13644283u,
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0u, 38047u, 9111839u,
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0u, 870u, 6138264u,
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0u, 14u, 12545723u,
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0u, 0u, 3104126u,
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0u, 0u, 28824u,
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0u, 0u, 198u,
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0u, 0u, 1u
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};
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uint32_t v0, v1, v2, hi;
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uint64_t lo;
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int z;
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/*
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* Get a random 72-bit value, into three 24-bit limbs v0..v2.
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*/
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lo = prng_get_u64(p);
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hi = prng_get_u8(p);
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v0 = (uint32_t)lo & 0xFFFFFF;
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v1 = (uint32_t)(lo >> 24) & 0xFFFFFF;
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v2 = (uint32_t)(lo >> 48) | (hi << 16);
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/*
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* Sampled value is z, such that v0..v2 is lower than the first
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* z elements of the table.
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*/
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uint32x4x3_t w;
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uint32x4_t x0, x1, x2, cc0, cc1, cc2, zz;
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uint32x2x3_t wh;
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uint32x2_t cc0h, cc1h, cc2h, zzh;
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x0 = vdupq_n_u32(v0);
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x1 = vdupq_n_u32(v1);
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x2 = vdupq_n_u32(v2);
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// 0: 0, 3, 6, 9
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// 1: 1, 4, 7, 10
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// 2: 2, 5, 8, 11
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// v0 - w0
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// v1 - w1
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// v2 - w2
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// cc1 - cc0 >> 31
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// cc2 - cc1 >> 31
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// z + cc2 >> 31
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w = vld3q_u32(&dist[0]);
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cc0 = vsubq_u32(x0, w.val[2]);
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cc1 = vsubq_u32(x1, w.val[1]);
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cc2 = vsubq_u32(x2, w.val[0]);
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cc1 = (uint32x4_t)vsraq_n_s32((int32x4_t)cc1, (int32x4_t)cc0, 31);
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cc2 = (uint32x4_t)vsraq_n_s32((int32x4_t)cc2, (int32x4_t)cc1, 31);
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zz = vshrq_n_u32(cc2, 31);
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w = vld3q_u32(&dist[12]);
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cc0 = vsubq_u32(x0, w.val[2]);
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cc1 = vsubq_u32(x1, w.val[1]);
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cc2 = vsubq_u32(x2, w.val[0]);
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cc1 = (uint32x4_t)vsraq_n_s32((int32x4_t)cc1, (int32x4_t)cc0, 31);
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cc2 = (uint32x4_t)vsraq_n_s32((int32x4_t)cc2, (int32x4_t)cc1, 31);
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zz = vsraq_n_u32(zz, cc2, 31);
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w = vld3q_u32(&dist[24]);
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cc0 = vsubq_u32(x0, w.val[2]);
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cc1 = vsubq_u32(x1, w.val[1]);
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cc2 = vsubq_u32(x2, w.val[0]);
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cc1 = (uint32x4_t)vsraq_n_s32((int32x4_t)cc1, (int32x4_t)cc0, 31);
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cc2 = (uint32x4_t)vsraq_n_s32((int32x4_t)cc2, (int32x4_t)cc1, 31);
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zz = vsraq_n_u32(zz, cc2, 31);
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w = vld3q_u32(&dist[36]);
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cc0 = vsubq_u32(x0, w.val[2]);
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cc1 = vsubq_u32(x1, w.val[1]);
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cc2 = vsubq_u32(x2, w.val[0]);
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cc1 = (uint32x4_t)vsraq_n_s32((int32x4_t)cc1, (int32x4_t)cc0, 31);
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cc2 = (uint32x4_t)vsraq_n_s32((int32x4_t)cc2, (int32x4_t)cc1, 31);
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zz = vsraq_n_u32(zz, cc2, 31);
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// 0: 48, 51
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// 1: 49, 52
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// 2: 50, 53
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wh = vld3_u32(&dist[48]);
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cc0h = vsub_u32(vget_low_u32(x0), wh.val[2]);
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cc1h = vsub_u32(vget_low_u32(x1), wh.val[1]);
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cc2h = vsub_u32(vget_low_u32(x2), wh.val[0]);
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cc1h = (uint32x2_t)vsra_n_s32((int32x2_t)cc1h, (int32x2_t)cc0h, 31);
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cc2h = (uint32x2_t)vsra_n_s32((int32x2_t)cc2h, (int32x2_t)cc1h, 31);
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zzh = vshr_n_u32(cc2h, 31);
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z = (int) (vaddvq_u32(zz) + vaddv_u32(zzh));
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return z;
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}
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/*
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* Sample a bit with probability exp(-x) for some x >= 0.
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*/
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static int
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BerExp(prng *p, fpr x, fpr ccs) {
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int s, i;
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fpr r;
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uint32_t sw, w;
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uint64_t z;
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/*
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* Reduce x modulo log(2): x = s*log(2) + r, with s an integer,
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* and 0 <= r < log(2). Since x >= 0, we can use fpr_trunc().
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*/
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s = (int)fpr_trunc(fpr_mul(x, fpr_inv_log2));
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r = fpr_sub(x, fpr_mul(fpr_of(s), fpr_log2));
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/*
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* It may happen (quite rarely) that s >= 64; if sigma = 1.2
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* (the minimum value for sigma), r = 0 and b = 1, then we get
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* s >= 64 if the half-Gaussian produced a z >= 13, which happens
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* with probability about 0.000000000230383991, which is
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* approximatively equal to 2^(-32). In any case, if s >= 64,
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* then BerExp will be non-zero with probability less than
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* 2^(-64), so we can simply saturate s at 63.
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*/
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sw = (uint32_t)s;
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sw ^= (sw ^ 63) & -((63 - sw) >> 31);
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s = (int)sw;
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/*
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* Compute exp(-r); we know that 0 <= r < log(2) at this point, so
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* we can use fpr_expm_p63(), which yields a result scaled to 2^63.
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* We scale it up to 2^64, then right-shift it by s bits because
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* we really want exp(-x) = 2^(-s)*exp(-r).
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*
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* The "-1" operation makes sure that the value fits on 64 bits
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* (i.e. if r = 0, we may get 2^64, and we prefer 2^64-1 in that
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* case). The bias is negligible since fpr_expm_p63() only computes
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* with 51 bits of precision or so.
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*/
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z = ((fpr_expm_p63(r, ccs) << 1) - 1) >> s;
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/*
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* Sample a bit with probability exp(-x). Since x = s*log(2) + r,
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* exp(-x) = 2^-s * exp(-r), we compare lazily exp(-x) with the
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* PRNG output to limit its consumption, the sign of the difference
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* yields the expected result.
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*/
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i = 64;
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do {
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i -= 8;
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w = prng_get_u8(p) - ((uint32_t)(z >> i) & 0xFF);
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} while (!w && i > 0);
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return (int)(w >> 31);
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}
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/*
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* The sampler produces a random integer that follows a discrete Gaussian
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* distribution, centered on mu, and with standard deviation sigma. The
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* provided parameter isigma is equal to 1/sigma.
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*
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* The value of sigma MUST lie between 1 and 2 (i.e. isigma lies between
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* 0.5 and 1); in Falcon, sigma should always be between 1.2 and 1.9.
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*/
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int
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PQCLEAN_FALCON512_AARCH64_sampler(void *ctx, fpr mu, fpr isigma) {
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sampler_context *spc;
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int s;
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fpr r, dss, ccs;
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spc = ctx;
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/*
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* Center is mu. We compute mu = s + r where s is an integer
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* and 0 <= r < 1.
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*/
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s = (int)fpr_floor(mu);
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r = fpr_sub(mu, fpr_of(s));
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/*
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* dss = 1/(2*sigma^2) = 0.5*(isigma^2).
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*/
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dss = fpr_half(fpr_sqr(isigma));
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/*
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* ccs = sigma_min / sigma = sigma_min * isigma.
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*/
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ccs = fpr_mul(isigma, spc->sigma_min);
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/*
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* We now need to sample on center r.
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*/
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for (;;) {
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int z0, z, b;
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fpr x;
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/*
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* Sample z for a Gaussian distribution. Then get a
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* random bit b to turn the sampling into a bimodal
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* distribution: if b = 1, we use z+1, otherwise we
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* use -z. We thus have two situations:
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*
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* - b = 1: z >= 1 and sampled against a Gaussian
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* centered on 1.
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* - b = 0: z <= 0 and sampled against a Gaussian
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* centered on 0.
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*/
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z0 = PQCLEAN_FALCON512_AARCH64_gaussian0_sampler(&spc->p);
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b = (int)prng_get_u8(&spc->p) & 1;
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z = b + ((b << 1) - 1) * z0;
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/*
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* Rejection sampling. We want a Gaussian centered on r;
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* but we sampled against a Gaussian centered on b (0 or
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* 1). But we know that z is always in the range where
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* our sampling distribution is greater than the Gaussian
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* distribution, so rejection works.
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*
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* We got z with distribution:
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* G(z) = exp(-((z-b)^2)/(2*sigma0^2))
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* We target distribution:
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* S(z) = exp(-((z-r)^2)/(2*sigma^2))
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* Rejection sampling works by keeping the value z with
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* probability S(z)/G(z), and starting again otherwise.
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* This requires S(z) <= G(z), which is the case here.
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* Thus, we simply need to keep our z with probability:
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* P = exp(-x)
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* where:
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* x = ((z-r)^2)/(2*sigma^2) - ((z-b)^2)/(2*sigma0^2)
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*
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* Here, we scale up the Bernouilli distribution, which
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* makes rejection more probable, but makes rejection
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* rate sufficiently decorrelated from the Gaussian
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* center and standard deviation that the whole sampler
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* can be said to be constant-time.
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*/
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x = fpr_mul(fpr_sqr(fpr_sub(fpr_of(z), r)), dss);
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x = fpr_sub(x, fpr_mul(fpr_of(z0 * z0), fpr_inv_2sqrsigma0));
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if (BerExp(&spc->p, x, ccs)) {
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/*
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* Rejection sampling was centered on r, but the
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* actual center is mu = s + r.
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*/
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return s + z;
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}
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}
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}
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