Data Privacy and Utility Trade-Off Based on Mutual Information Neural Estimator

TL;DR

This paper introduces a neural network-based method to accurately estimate mutual information for balancing data privacy and utility, especially with limited samples, improving privacy-preserving data sharing.

Contribution

It proposes a novel privacy funnel framework using Mutual Information Neural Estimator (MINE) to better quantify and optimize privacy-utility trade-offs in data sharing.

Findings

MINE accurately estimates mutual information with limited samples.

The method effectively balances privacy and utility in data sharing.

Simulation results validate the approach's effectiveness.

Abstract

In the era of big data and the Internet of Things (IoT), data owners need to share a large amount of data with the intended receivers in an insecure environment, posing a trade-off issue between user privacy and data utility. The privacy utility trade-off was facilitated through a privacy funnel based on mutual information. Nevertheless, it is challenging to characterize the mutual information accurately with small sample size or unknown distribution functions. In this article, we propose a privacy funnel based on mutual information neural estimator (MINE) to optimize the privacy utility trade-off by estimating mutual information. Instead of computing mutual information in traditional way, we estimate it using an MINE, which obtains the estimated mutual information in a trained way, ensuring that the estimation results are as precise as possible. We employ estimated mutual information as a measure of privacy and utility, and then form a problem to optimize data utility by training a neural network while the estimator's privacy discourse is less than a threshold. The simulation results also demonstrated that the estimated mutual information from MINE works very well to approximate the mutual information even with a limited number of samples to quantify privacy leakage and data utility retention, as well as optimize the privacy utility trade-off.