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# Copyright 2020 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
#
# http://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.
"""Basic Example for Using Privacy Loss Distributions.
"""
from absl import app
from dp_accounting import privacy_loss_distribution
def main(argv):
if len(argv) > 1:
raise app.UsageError('Too many command-line arguments.')
# The parameter of Laplace Noise added
parameter_laplace = 3
# PLD for one execution of the Laplace Mechanism. (Throughout we assume that
# sensitivity = 1.)
laplace_pld = privacy_loss_distribution.PrivacyLossDistribution.from_laplace_mechanism(
parameter_laplace, value_discretization_interval=1e-3)
# Number of times Laplace Mechanism is run
num_laplace = 40
# PLD for num_laplace executions of the Laplace Mechanism.
composed_laplace_pld = laplace_pld.self_compose(num_laplace)
epsilon = 10
delta = composed_laplace_pld.get_delta_for_epsilon(epsilon)
print(f'An algorithm that executes the Laplace Mechanism with parameter '
f'{parameter_laplace} for a total of {num_laplace} times is '
f'({epsilon}, {delta})-DP.')
# PLDs for different mechanisms can also be composed. Below is an example in
# which we compose PLDs for Laplace Mechanism and Gaussian Mechanism.
# STD of the Gaussian Noise
standard_deviation = 5
# PLD for an execution of the Gaussian Mechanism.
gaussian_pld = privacy_loss_distribution.PrivacyLossDistribution.from_gaussian_mechanism(
standard_deviation, value_discretization_interval=1e-3)
# PLD for num_laplace executions of the Laplace Mechanism and one execution of
# the Gaussian Mechanism.
composed_laplace_and_gaussian_pld = composed_laplace_pld.compose(gaussian_pld)
epsilon = 10
delta = composed_laplace_and_gaussian_pld.get_delta_for_epsilon(epsilon)
print(f'An algorithm that executes the Laplace Mechanism with parameter '
f'{parameter_laplace} for a total of {num_laplace} times and in '
f'addition executes once the Gaussian Mechanism with STD '
f'{standard_deviation} is ({epsilon}, {delta})-DP.')
if __name__ == '__main__':
app.run(main)