A Systematic Exploration of Text Decomposition and Budget Distribution in Differentially Private Text Obfuscation

TL;DR

This paper systematically evaluates how different text decomposition and privacy budget distribution methods impact the effectiveness of differentially private text obfuscation, highlighting the importance of design choices.

Contribution

It provides a comprehensive analysis of text chunking and budget allocation strategies, demonstrating their significant influence on privacy-utility trade-offs in DP text obfuscation.

Findings

Different decomposition and budget distribution methods lead to significantly different results.

Optimizing text chunking and budget allocation can improve empirical privacy-utility trade-offs.

Design choices in DP text obfuscation are crucial for achieving better performance.

Abstract

The goal of differentially private text obfuscation is to obfuscate, or "perturb", input texts with Differential Privacy (DP) guarantees, such that the private output texts are quantifiably indistinguishable from the originals. While perturbation at the word level is intuitive, meaningful text privatization happens on complete documents. Recent research has laid the groundwork for reasoning about privacy budget distribution, namely, how an overall $\varepsilon$ budget can be sensibly distributed among the component pieces of a text. We perform a systematic evaluation of multiple text decomposition and budget distribution techniques in the context of DP text obfuscation, testing how different methods for chunking texts can be combined with techniques for allocating $\varepsilon$ to these chunks. Our experiments reveal that such design choices are very important, as even with comparable privacy budgets, significantly different results can occur based on which methods are chosen. In this, we provide credible evidence of the feasibility of maximizing empirical trade-offs by optimizing DP obfuscation procedures.