Guide to Differential Privacy Modifications : A Taxonomy of Variants and Extensions / by Balázs Pejó, Damien Desfontaines.

Format:

Book

Author/Creator:

Pejó, Balázs., Author.

Desfontaines, Damien., Author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

SpringerBriefs in computer science 2191-5776

SpringerBriefs in Computer Science, 2191-5776

Language:

English

Subjects (All):

Data protection-Law and legislation.

Data protection.

Cryptography.

Data encryption (Computer science).

Privacy.

Data and Information Security.

Cryptology.

Local Subjects:

Privacy.

Data and Information Security.

Cryptology.

Physical Description:

1 online resource (VIII, 89 pages) : 2 illustrations

Edition:

1st ed. 2022.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2022.

System Details:

text file PDF

Summary:

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 collecting existing ones.

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.

Other Format:

Printed edition:

ISBN:

978-3-030-96398-9

9783030963989

Access Restriction:

Restricted for use by site license.