Guide to Differential Privacy Modifications: A Taxonomy of Variants and Extensions
Shortly after it was first introduced in 2006, differential privacy became the flagship data privacy definition. Since then, numerous variants and extensions were proposed to adapt it to different scenarios and attacker models. In this work, we propose a systematic taxonomy of these variants and extensions. We list all data privacy definitions based on differential privacy, and partition them into seven categories, depending on which aspect of the original definition is modified.
These categories act like dimensions: Variants from the same category cannot be combined, but variants from different categories can be combined to form new definitions. We also establish a partial ordering of relative strength between these notions by summarizing existing results. Furthermore, we list which of these definitions satisfy some desirable properties, like composition, post-processing, and convexity by either providing a novel proof or collectingexisting ones.
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Guide to Differential Privacy Modifications: A Taxonomy of Variants and Extensions
Shortly after it was first introduced in 2006, differential privacy became the flagship data privacy definition. Since then, numerous variants and extensions were proposed to adapt it to different scenarios and attacker models. In this work, we propose a systematic taxonomy of these variants and extensions. We list all data privacy definitions based on differential privacy, and partition them into seven categories, depending on which aspect of the original definition is modified.
These categories act like dimensions: Variants from the same category cannot be combined, but variants from different categories can be combined to form new definitions. We also establish a partial ordering of relative strength between these notions by summarizing existing results. Furthermore, we list which of these definitions satisfy some desirable properties, like composition, post-processing, and convexity by either providing a novel proof or collectingexisting ones.
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Guide to Differential Privacy Modifications: A Taxonomy of Variants and Extensions

Guide to Differential Privacy Modifications: A Taxonomy of Variants and Extensions

Guide to Differential Privacy Modifications: A Taxonomy of Variants and Extensions

Guide to Differential Privacy Modifications: A Taxonomy of Variants and Extensions

eBook1st ed. 2022 (1st ed. 2022)

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Overview

Shortly after it was first introduced in 2006, differential privacy became the flagship data privacy definition. Since then, numerous variants and extensions were proposed to adapt it to different scenarios and attacker models. In this work, we propose a systematic taxonomy of these variants and extensions. We list all data privacy definitions based on differential privacy, and partition them into seven categories, depending on which aspect of the original definition is modified.
These categories act like dimensions: Variants from the same category cannot be combined, but variants from different categories can be combined to form new definitions. We also establish a partial ordering of relative strength between these notions by summarizing existing results. Furthermore, we list which of these definitions satisfy some desirable properties, like composition, post-processing, and convexity by either providing a novel proof or collectingexisting ones.

Product Details

ISBN-13: 9783030963989
Publisher: Springer-Verlag New York, LLC
Publication date: 04/09/2022
Series: SpringerBriefs in Computer Science
Sold by: Barnes & Noble
Format: eBook
File size: 4 MB

Table of Contents

1. Introduction.- 2. Differential Privacy.- 3. Quantification of privacy loss.- 4. Neighborhood definition (N).- 5. Variation of privacy loss (V).- 6.  Background knowledge (B).- 7. Change in formalism (F).- 8. Relativization of the knowledge gain (R).- 9. Computational power (C).- 10. Summarizing table.- 11.  Scope and related work.- 12. Conclusion.
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