Privacy and Anonymity in Information Management Systems - New Techniques for New Practical Problems

Foreword

Acknowledgments

Contents

Contributors

Part I Overview

1 Introduction to Privacy and Anonymity in Information Management Systems

1.1 Background and Motivation

1.2 Organization of the Book

1.2.1 Part II: Theory of SDC

1.2.2 Part III: Preserving Privacy in Distributed Applications

2 Advanced Privacy-Preserving Data Managementand Analysis

2.1 Introduction

2.2 Managing Anonymized Data

2.2.1 Randomization-Based Anonymization Techniques

2.2.2 Aggregation-Based Anonymization Techniques

2.3 Managing Time-Varying Anonymized Data

2.3.1 Anonymizing Multiple Releases

2.3.2 Anonymizing Data Streams

2.4 Privacy-Preserving Data Analysis (PPDA)

2.4.1 Privacy-Preserving Association Rule Mining

2.4.2 Privacy-Preserving Classification

2.4.3 Privacy-Preserving Clustering

2.5 Conclusions

References

Part II Theory of SDC

3 Practical Applications in Statistical Disclosure ControlUsing R

3.1 Microdata Protection Using sdcMicro

3.1.1 Software Issues

3.1.2 The sdcMicro GUI

3.1.3 Anonymization of Categorical Variables

3.1.4 Anonymization of Numerical Variables

3.1.5 Disclosure Risk

3.1.6 Case Study Using Real-World Data

3.2 Tabular Data Protection Using sdcTable

3.2.1 Frequency and Magnitude Tables

3.2.2 Primary Sensitive Cells

3.2.3 Secondary Cell Suppression

3.2.4 Software Issues

3.2.5 Anonymizing Tables Using sdcTable -- A Guided Tour

3.2.6 Summary

3.3 Summary

References

4 Disclosure Risk Assessment for Sample Microdata Through Probabilistic Modeling

4.1 Introduction

4.2 Disclosure Risk Measures and Their Estimation

4.2.1 Notation and Definitions

4.2.2 Estimating the Disclosure Risk

4.2.3 Model Selection and Goodness-of-Fit Criteria

4.3 Complex Survey Designs

4.4 Measurement Error Models for Disclosure Risk Measures

4.5 Variance Estimation for Global Disclosure Risk Measures

4.6 Examples of Applications

4.6.1 Estimating Disclosure Risk Measures Under No Misclassification

4.6.2 Estimating Disclosure Risk Measures Under Misclassification

4.6.3 Variance Estimation and Confidence Intervals

4.7 Extensions to Probabilistic Modeling for Disclosure Risk Estimation

References

5 Exploiting Auxiliary Information in the Estimation of Per-Record Risk of Disclosure

5.1 Introduction

5.2 Risk Measures and Models for Risk Estimation

5.2.1 Superpopulation Models for Risk Estimation with Survey Data

5.2.2 SPREE-Type Estimators for Cross-Classifications

5.3 Simulation Plan and Data

5.4 Risk Estimators and Simulation Results

5.5 Comments

References

6 Statistical Disclosure Control in Tabular Data

6.1 Introduction

6.2 Tabular Data: Types and Modeling

6.2.1 Classification of Tables

6.2.2 Modeling Tables

6.3 Sensitive Cells and Sensitivity Rules

6.3.1 The Threshold Rule for Frequency Tables

6.3.2 The (n,k) and p% Rules for Magnitude Tables

6.4 Tabular Data Protection Methods

6.4.1 Recoding

6.4.2 Cell Suppression

6.4.3 Controlled Rounding

6.4.4 Controlled Tabular Adjustment

6.5 Conclusions

References

Part III Preserving Privacy in Distributed Applications

7 From Collaborative to Privacy-Preserving SequentialPattern Mining

7.1 Introduction

7.2 Problem Statement

7.2.1 Mining of Sequential Patterns

7.2.2 From Collaborative to Privacy-Preserving Sequential Pattern Mining

7.3 The PRIPSEP Approach

7.3.1 Collaborative Sequential Pattern Mining

7.3.2 From Collaborative to Privacy-Preserving Sequential Pattern Mining

7.3.3 Improving the Robustness of the System

7.4 Conclusion

References

8 Pseudonymized Data Sharing

8.1 Introduction

8.1.1 Security Properties

8.1.2 Relevance

8.1.3 Related Work

8.2 Description of a Pseudonymized Data Sharing System

8.2.1 Syntax

8.2.2 Security Requirements

8.2.3 Notation

8.3 Basic Tools

8.3.1 Symmetric Encryption with Semantic Security

8.3.2 Decisional Diffie--Hellman Assumption

8.3.3 Pairings

8.3.4 Commutative Encryption

8.3.5 Intersection Protocol

8.4 A Pseudonym Scheme with Ubiquitous TTP

8.5 A Basic Pseudonym Scheme with Light TTP

8.6 A Fully Secure Pseudonym Scheme with Light TTP

8.7 Conclusion

References

9 Privacy-Aware Access Control in Social Networks: Issues and Solutions

9.1 Introduction

9.2 Access Control Requirements

9.3 Privacy Issues in OSN Access Control

9.4 Review of the Literature

9.4.1 Access Control Models

9.4.2 Privacy-Aware Access Control

9.5 Conclusions and Future Research Directions

References

Index