Distributed Differential Privacy By Sampling

In this paper, we describe our approach to achieve distributed differential privacy by sampling alone. Our mechanism works in the semihonest setting (honest-but-curious whereby aggregators attempt to peek at the data though follow the protocol). We show that the utility remains constant and does not degrade due to the variance as compared to the randomized response mechanism. In addition, we show smaller privacy leakage as compared to the randomized response mechanism.