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

Author:   Balázs Pejó ,  Damien Desfontaines
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2022
ISBN:  

9783030963972


Pages:   89
Publication Date:   10 April 2022
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Guide to Differential Privacy Modifications: A Taxonomy of Variants and Extensions


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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.

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Author:   Balázs Pejó ,  Damien Desfontaines
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2022
Weight:   0.168kg
ISBN:  

9783030963972


ISBN 10:   3030963977
Pages:   89
Publication Date:   10 April 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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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