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Erschienen in:
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2020 | OriginalPaper | Buchkapitel

1. Defining Privacy-Preserving Data Analysis

verfasst von : Jerome Le Ny

Erschienen in: Differential Privacy for Dynamic Data

Verlag: Springer International Publishing

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Abstract

With the growing focus on instrumenting our environment and monitoring our activities, there is a need to implement privacy-preserving algorithms into our technological systems. Defining privacy formally is a delicate task but is a necessary first step to be able to provide clear guarantees to the individuals being monitored. In this chapter, after discussing the pitfalls of naive approaches to data privacy, we review the notion of differential privacy, a state-of-the-art definition of privacy that we adopt in the rest of this monograph, and which provides guarantees against adversaries with arbitrary side information. Privacy-preserving data analysis has a relatively long history in fields such as econometrics and statistics or for the processing of sensitive static data stored for example in medical databases. Current trends emphasize the need to work with streams of data originating from many sources and requiring sanitization in real-time, which brings new challenges to the field.

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Nächstes Kapitel Basic Differentially Private Mechanisms
Fußnoten
1
More formally, fix some probability space \((\Omega , \mathscr {F}, \mathbb P)\). Then a mechanism is a map \(M: \mathsf U\times \Omega \rightarrow \mathsf Y\), and we abbreviate the notation \(M(u,\omega )\) by M(u), following the standard practice used to denote random variables.
 
2
This is sometimes implicitly done in the literature by “normalizing the dataset”, assuming a priori that each individual’s numerical data belong to a known bounded set for example.
 
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Metadaten
Titel
Defining Privacy-Preserving Data Analysis
verfasst von
Jerome Le Ny
Copyright-Jahr
2020
Buch
Differential Privacy for Dynamic Data

Print ISBN: 978-3-030-41038-4

Electronic ISBN: 978-3-030-41039-1

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-41039-1_1

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