Biometric Security and Privacy Opportunities & Challenges in The Big Data Era
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 quality issue, biometric template prote...
| Other Authors: | , , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2017, 2017
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| Edition: | 1st ed. 2017 |
| Series: | Signal Processing for Security Technologies
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
| Summary: | 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 quality issue, biometric template protection, and anti-spoofing. The book also focuses on several emerging topics such as big data issues, mobile biometrics and multispectral biometrics, and includes a number of new biometrics such as vein pattern, acoustic biometrics, eye-blinking EOG, ECG, gait and handwriting. Authors also show how to use biometrics in cyber security applications and its relevant legal matters under EU legislation. The contributors cover the topics, their methods, and their applications in depth |
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| Physical Description: | VIII, 424 p. 194 illus., 146 illus. in color online resource |
| ISBN: | 9783319473017 |