A layered perturbation method for the protection of tabular outputs
Section 1. Introduction

Table of contents

Statistical agencies are under pressure to provide more information from their data holdings to external users. Many now enable the creation of custom tables through on-line query systems. But the risks of a disclosure of confidential information increase with the quantity of outputs released. To address this problem agencies can go from one extreme, which is to severely limit the amount of information being released, to another, which is to generate outputs from model-based synthetic microdata. Perturbative methods, which add noise to microdata or aggregate results, lie somewhere in between. This paper proposes a perturbative method for quantitative administrative data, such as personal taxation data, in a custom tabulation environment. Section 2 provides some background information, outlines desirable objectives and reviews standard approaches for the protection of tables of magnitude. Section 3 presents the proposed Layered Perturbation Method (LPM) and provides some of its properties. An empirical evaluation is given in Section 4 and outstanding issues are discussed in Section 5.

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Table of contents

Abstract - Article main page
Section 1. Introduction
Section 2. Background
Section 3. The Layered Perturbation Method (LPM)
Section 4. Empirical investigation
Section 5. Discussion and challenges
References

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