Biometric Security and Privacy - Opportunities & Challenges in The Big Data Era (Hardcover, 1st ed. 2017)


This book highlights recent research advances on biometrics using new methods such as deep learning, nonlinear graph embedding, fuzzy approaches, and ensemble learning. Included are special biometric technologies related to privacy and security issues, such as cancellable biometrics and soft biometrics. The book also focuses on several emerging topics such as big data issues, internet of things, medical biometrics, healthcare, and robot-human interactions. The authors show how these new applications have triggered a number of new biometric approaches. They show, as an example, how fuzzy extractor has become a useful tool for key generation in biometric banking, and vein/heart rates from medical records can also be used to identify patients. The contributors cover the topics, their methods, and their applications in depth.

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Product Description

This book highlights recent research advances on biometrics using new methods such as deep learning, nonlinear graph embedding, fuzzy approaches, and ensemble learning. Included are special biometric technologies related to privacy and security issues, such as cancellable biometrics and soft biometrics. The book also focuses on several emerging topics such as big data issues, internet of things, medical biometrics, healthcare, and robot-human interactions. The authors show how these new applications have triggered a number of new biometric approaches. They show, as an example, how fuzzy extractor has become a useful tool for key generation in biometric banking, and vein/heart rates from medical records can also be used to identify patients. The contributors cover the topics, their methods, and their applications in depth.

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Product Details

General

Imprint

Springer International Publishing AG

Country of origin

Switzerland

Series

Signal Processing for Security Technologies

Release date

December 2016

Availability

Expected to ship within 12 - 17 working days

First published

2017

Editors

, , , ,

Dimensions

235 x 155 x 26mm (L x W x T)

Format

Hardcover

Pages

424

Edition

1st ed. 2017

ISBN-13

978-3-319-47300-0

Barcode

9783319473000

Categories

LSN

3-319-47300-X



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