Managing Differential Privacy in Large Scale Systems
Abhishek Tiwari
SEPTEMBER 21, 2024
The promise of differential privacy is compelling. It offers a rigorous, provable guarantee of individual privacy, even in the face of arbitrary background knowledge. Rather than relying on anonymization techniques that can often be defeated, differential privacy works by injecting carefully calibrated noise into computations. This allows aggregate statistics and insights to be extracted from data while masking the contributions of any single individual.
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