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"""privacy.py module."""
import tensorflow_privacy as tfp
from typing import Dict, Any
import numpy as np
class PrivacyManager:
def __init__(self, config: Dict[str, Any]):
self.epsilon = config['privacy']['epsilon']
self.delta = config['privacy']['delta']
self.noise_multiplier = config['privacy']['noise_multiplier']
def add_noise_to_gradients(self, gradients: np.ndarray) -> np.ndarray:
"""Add Gaussian noise to gradients for differential privacy."""
noise = np.random.normal(0, self.noise_multiplier, gradients.shape)
return gradients + noise
def verify_privacy_budget(self, num_iterations: int) -> bool:
"""Check if training stays within privacy budget."""
eps = self.compute_epsilon(num_iterations)
return eps <= self.epsilon
def compute_epsilon(self, num_iterations: int) -> float:
"""Compute the current epsilon value."""
q = 1.0 # sampling ratio
steps = num_iterations
orders = ([1.25, 1.5, 1.75, 2., 2.25, 2.5, 3., 3.5, 4., 4.5] +
list(range(5, 64)) + [128, 256, 512])
return tfp.compute_dp_sgd_privacy(
n=1000, # number of training points
batch_size=32,
noise_multiplier=self.noise_multiplier,
epochs=steps,
delta=self.delta
)[0]
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