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Pim Tuyls, Boris Skoric, Tom Kevenaar - Security with Noisy Data: On Private Biometrics, Secure Key Storage and Anti-Counterfeiting
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Noisy data appears very naturally in applications where the authentication is based on physical identifiers, such as human beings, or physical structures, such as physical unclonable functions. This book examines how the presence of noise has an impact on information security, describes how it can be dealt with and possibly used to generate an advantage over traditional approaches, and provides a self-contained overview of the techniques and applications of security based on noisy data.
Security with Noisy Data thoroughly covers the theory of authentication based on noisy data and shows it in practice as a key tool for preventing counterfeiting. Part I discusses security primitives that allow noisy inputs, and Part II focuses on the practical applications of the methods discussed in the first part.
Key features:
Contains algorithms to derive secure keys from noisy data, in particular from physical unclonable functions and biometrics - as well as the theory proving that those algorithms are secure
Offers practical implementations of algorithms, including techniques that give insight into system security
Includes an overview and detailed description of new applications made possible by using these new algorithms
Discusses recent theoretical as well as application-oriented developments in the field, combining noisy data with cryptography
Describes the foundations of the subject in a clear, accessible and reader-friendly style
Presents the principles of key establishment and multiparty computation over noisy channels
Provides a detailed overview of the building blocks of cryptography for noisy data and explains how these techniques can be applied, (for example as anti-counterfeiting and key storage)
Introduces privacy protected biometric systems, analyzes the theoretical and practical properties of PUFs and discusses PUF based systems
Addresses biometrics and physical unclonable functions extensively
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