A Tutorial on Computing $t$-Closeness

TL;DR

This tutorial explains how to compute $t$-closeness, a privacy measure in data publishing, with detailed examples, calculations, and an efficient algorithm for practical implementation.

Contribution

It provides the first comprehensive tutorial with detailed examples and an efficient algorithm for computing $t$-closeness, enhancing understanding and practical application.

Findings

Detailed step-by-step examples of $t$-closeness computation

Introduction of an efficient algorithm for $t$-closeness calculation

Clarification of the use of earth mover's distance in privacy measures

Abstract

This paper presents a tutorial of the computation of $t$-closeness. An established model in the domain of privacy preserving data publishing, $t$-closeness is a measure of the earth mover's distance between two distributions of an anonymized database table. This tutorial includes three examples that showcase the full computation of $t$-closeness in terms of both numerical and categorical attributes. Calculations are carried out using the definition of the earth mover's distance and weighted order distance. This paper includes detailed explanations and calculations not found elsewhere in the literature. An efficient algorithm to calculate the $t$-closeness of a table is also presented.