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Differential privacy for dynamic data /

Le Ny, Jerome.

Differential privacy for dynamic data /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Differential privacy for dynamic data // Jerome Le Ny.
Author:	Le Ny, Jerome.
Published:	Cham :Springer,c2020.
Description:	xi,110 p. :ill.(some col.), charts ;24 cm.
Subject:	Data protection. -
ISBN:	9783030410384 (pbk.) :
ISBN:	3030410382 (pbk.)

Differential privacy for dynamic data /
Le Ny, Jerome.

Differential privacy for dynamic data /Jerome Le Ny. - Cham :Springer,c2020. - xi,110 p. :ill.(some col.), charts ;24 cm. - SpringerBriefs in electrical and computer engineering. Control, automation and robotics. - SpringerBriefs in electrical and computer engineering..

Includes bibliographical references.

This Springer brief provides the necessary foundations to understand differential privacy and describes practical algorithms enforcing this concept for the publication of real-time statistics based on sensitive data. Several scenarios of interest are considered, depending on the kind of estimator to be implemented and the potential availability of prior public information about the data, which can be used greatly to improve the estimators' performance. The brief encourages the proper use of large datasets based on private data obtained from individuals in the world of the Internet of Things and participatory sensing. For the benefit of the reader, several examples are discussed to illustrate the concepts and evaluate the performance of the algorithms described. These examples relate to traffic estimation, sensing in smart buildings, and syndromic surveillance to detect epidemic outbreaks.

ISBN: 9783030410384 (pbk.) :NT1200Subjects--Topical Terms:

154030
Data protection.

LC Class. No.: QA76.9.A25

Dewey Class. No.: 005.8

Differential privacy for dynamic data /
LDR:01830cam a2200265 i 4500 001 1000105749
003 OCoLC
005 20200417035436.2
008 201104s2020 sz ad g b 000 0 eng d
020 $a 9783030410384 (pbk.) : $c NT1200
020 $a 3030410382 (pbk.)
020 $z 9783030410391 (ebk.)
020 $z 3030410390 (ebk.)
035 $a (OCoLC)1147270967
035 $a 1147270967
040 $a YDX $b eng $c YDX $d GW5XE
050 # 4 $a QA76.9.A25
082 0 4 $a 005.8 $2 23
100 1 $a Le Ny, Jerome. $3 1000130828
245 1 0 $a Differential privacy for dynamic data / $c Jerome Le Ny.
260 # $a Cham : $b Springer, $c c2020.
300 $a xi,110 p. : $b ill.(some col.), charts ; $c 24 cm.
490 1 $a SpringerBriefs in electrical and computer engineering. Control, automation and robotics
490 1 $a SpringerBriefs in electrical and computer engineering, $x 2191-8112
490 1 $a SpringerBriefs in control, automation and robotics, $x 2192-6786
504 $a Includes bibliographical references.
520 # $a This Springer brief provides the necessary foundations to understand differential privacy and describes practical algorithms enforcing this concept for the publication of real-time statistics based on sensitive data. Several scenarios of interest are considered, depending on the kind of estimator to be implemented and the potential availability of prior public information about the data, which can be used greatly to improve the estimators' performance. The brief encourages the proper use of large datasets based on private data obtained from individuals in the world of the Internet of Things and participatory sensing. For the benefit of the reader, several examples are discussed to illustrate the concepts and evaluate the performance of the algorithms described. These examples relate to traffic estimation, sensing in smart buildings, and syndromic surveillance to detect epidemic outbreaks.
650 # 0 $a Data protection. $3 154030
650 # 0 $a Filters (Mathematics) $3 169457
650 # 0 $a Stochastic processes. $3 146788
650 # 0 $a Privacy, Right of. $3 150220
830 0 $a SpringerBriefs in electrical and computer engineering. $3 1000002263
830 0 $a SpringerBriefs in electrical and computer engineering, $x 2191-8112. $3 1000130829
830 0 $a SpringerBriefs in control, automation and robotics, $x 2192-6786. $3 1000130830