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Guide to Differential Privacy Modifications: A Taxonomy of Variants and Extensions: SpringerBriefs in Computer Science

Autor Balázs Pejó, Damien Desfontaines
en Limba Engleză Paperback – 10 apr 2022
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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Specificații

ISBN-13: 9783030963972
ISBN-10: 3030963977
Pagini: 89
Ilustrații: VIII, 89 p. 2 illus.
Dimensiuni: 155 x 235 x 9 mm
Greutate: 0.15 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Seria SpringerBriefs in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

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.

Caracteristici

Offers a systematic approach to differential privacy Addresses quantification and variation of privacy loss Lists and categorises privacy definitions