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/*
* Copyright 2019 Google LLC.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "private_join_and_compute/crypto/simultaneous_fixed_bases_exp.h"
#include <algorithm>
#include <cstddef>
#include <memory>
#include <utility>
#include <vector>
#include "absl/memory/memory.h"
#include "absl/strings/str_cat.h"
#include "private_join_and_compute/crypto/big_num.h"
#include "private_join_and_compute/crypto/mont_mul.h"
#include "private_join_and_compute/util/status.inc"
namespace private_join_and_compute {
namespace internal {
template <typename Element>
StatusOr<Element> Clone(const Element& element);
template <typename Element, typename Context>
StatusOr<Element> Mul(const Element& e1, const Element& e2,
const Context& context);
template <typename Element>
bool IsZero(const Element& c);
template <>
StatusOr<private_join_and_compute::BigNum> Clone(
const private_join_and_compute::BigNum& element) {
return element;
}
template <>
bool IsZero(const private_join_and_compute::BigNum& c) {
return c.IsOne();
}
template <>
StatusOr<ZnElement> Mul(const ZnElement& e1, const ZnElement& e2,
const ZnContext& context) {
return e1.ModMul(e2, context.modulus);
}
template <>
StatusOr<private_join_and_compute::MontBigNum> Clone(
const private_join_and_compute::MontBigNum& element) {
return element;
}
template <>
StatusOr<private_join_and_compute::MontBigNum> Mul(
const private_join_and_compute::MontBigNum& e1,
const private_join_and_compute::MontBigNum& e2,
const private_join_and_compute::MontContext& context) {
return e1.Mul(e2);
}
template <>
bool IsZero(const private_join_and_compute::MontBigNum& c) {
return c.ToBigNum().IsOne();
}
} // namespace internal
template <typename Element, typename Context>
SimultaneousFixedBasesExp<Element, Context>::SimultaneousFixedBasesExp(
size_t num_bases, size_t num_simultaneous, size_t num_batches,
std::unique_ptr<Element> zero, std::unique_ptr<Context> context,
std::vector<std::vector<std::unique_ptr<Element>>> table)
: num_bases_(num_bases),
num_simultaneous_(num_simultaneous),
num_batches_(num_batches),
zero_(std::move(zero)),
context_(std::move(context)),
precomputed_table_(std::move(table)) {}
template <typename Element, typename Context>
StatusOr<std::unique_ptr<SimultaneousFixedBasesExp<Element, Context>>>
SimultaneousFixedBasesExp<Element, Context>::Create(
const std::vector<Element>& bases, const Element& zero,
size_t num_simultaneous, std::unique_ptr<Context> context) {
if (num_simultaneous == 0) {
return absl::InvalidArgumentError(
absl::StrCat("The num_simultaneous parameter, ", num_simultaneous,
", should be positive."));
}
if (num_simultaneous > bases.size()) {
return absl::InvalidArgumentError(absl::StrCat(
"The num_simultaneous parameter, ", num_simultaneous,
", can be at most the number of bases", bases.size(), "."));
}
size_t num_batches = (bases.size() + num_simultaneous - 1) / num_simultaneous;
ASSIGN_OR_RETURN(auto zero_clone, internal::Clone(zero));
std::unique_ptr<Element> zero_ptr =
std::make_unique<Element>(std::move(zero_clone));
ASSIGN_OR_RETURN(std::vector<std::vector<std::unique_ptr<Element>>> table,
SimultaneousFixedBasesExp::Precompute(
bases, zero, *context, num_simultaneous, num_batches));
return absl::WrapUnique<SimultaneousFixedBasesExp>(
new SimultaneousFixedBasesExp(bases.size(), num_simultaneous, num_batches,
std::move(zero_ptr), std::move(context),
std::move(table)));
}
template <typename Element, typename Context>
StatusOr<std::vector<std::vector<std::unique_ptr<Element>>>>
SimultaneousFixedBasesExp<Element, Context>::Precompute(
const std::vector<Element>& bases, const Element& zero,
const Context& context, size_t num_simultaneous, size_t num_batches) {
std::vector<std::vector<std::unique_ptr<Element>>> table;
for (size_t i = 0; i < num_batches; ++i) {
table.push_back({});
ASSIGN_OR_RETURN(Element zero_clone, internal::Clone(zero));
table[i].push_back(std::make_unique<Element>(std::move(zero_clone)));
const size_t start = i * num_simultaneous;
const size_t num_items_in_batch =
std::min(bases.size() - start, num_simultaneous);
int highest_one_bit = 0;
// Generate all values (c1, ..., ck) in {0, 1}^k using the binary
// representation of integers between [0, 2^k - 1].
for (int j = 1; j < (1 << num_items_in_batch); ++j) {
if (j & (1 << (highest_one_bit + 1))) {
++highest_one_bit;
}
size_t prev = j - (1 << highest_one_bit);
if (prev == 0) {
ASSIGN_OR_RETURN(Element clone,
internal::Clone(bases[start + highest_one_bit]));
table[i].push_back(std::make_unique<Element>(std::move(clone)));
} else {
ASSIGN_OR_RETURN(
Element add,
internal::Mul(*(table[i][prev]), bases[start + highest_one_bit],
context));
table[i].push_back(std::make_unique<Element>(std::move(add)));
}
}
}
return std::move(table);
}
template <typename Element, typename Context>
StatusOr<Element> SimultaneousFixedBasesExp<Element, Context>::SimultaneousExp(
const std::vector<private_join_and_compute::BigNum>& exponents) const {
if (exponents.size() != num_bases_) {
return absl::InvalidArgumentError(
absl::StrCat("Number of exponents, ", exponents.size(), ", and bases,",
num_bases_, ", are not equal."));
}
int max_bit_length = 0;
for (const auto& exponent : exponents) {
if (exponent.BitLength() > max_bit_length) {
max_bit_length = exponent.BitLength();
}
}
ASSIGN_OR_RETURN(Element result, internal::Clone(*zero_));
for (int i = max_bit_length - 1; i >= 0; --i) {
if (!internal::IsZero(result)) {
ASSIGN_OR_RETURN(result, internal::Mul(result, result, *context_));
}
for (size_t j = 0; j < num_batches_; ++j) {
size_t precompute_idx = 0;
size_t batch_size = num_simultaneous_;
if (batch_size > num_bases_ - (j * num_simultaneous_)) {
batch_size = num_bases_ - (j * num_simultaneous_);
}
for (size_t k = 0; k < batch_size; ++k) {
size_t data_idx = (j * num_simultaneous_) + k;
if (exponents[data_idx].IsBitSet(i)) {
precompute_idx += (1 << k);
}
}
if (precompute_idx) {
ASSIGN_OR_RETURN(
result,
internal::Mul(result, *(precomputed_table_[j][precompute_idx]),
*context_));
}
}
}
return std::move(result);
}
template class SimultaneousFixedBasesExp<private_join_and_compute::MontBigNum,
private_join_and_compute::MontContext>;
template class SimultaneousFixedBasesExp<ZnElement, ZnContext>;
} // namespace private_join_and_compute
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