RWN: A Novel Neighborhood-Based Method for Statistical Disclosure Control

TL;DR

This paper introduces RWN, a new neighborhood-based data swapping method for statistical disclosure control that preserves multivariate data relations, supported by a theorem and extensive empirical evaluation.

Contribution

It presents a novel variation of data swapping that maintains multivariate relationships, supported by theoretical proof and empirical testing.

Findings

The method effectively preserves multivariate data structures.

Theoretical proof supports the validity of the approach.

Empirical results demonstrate improved disclosure control.

Abstract

A novel variation of the data swapping approach to statistical disclosure control is presented, aimed particularly at preservation of multivariate relations in the original dataset. A theorem is proved in support of the method, and extensive empirical investigation is reported.