Security with Noisy Data [electronic resource] : On Private Biometrics, Secure Key Storage and Anti-Counterfeiting /
Tuyls, Pim.editor.
Škoric, Boris.editor.
Kevenaar, Tom.editor.
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 This comprehensive introduction offers an excellent foundation to graduate students and researchers entering the field, and will also benefit professionals needing to expand their knowledge. Readers will gain a well-rounded and broad understanding of the topic through the insight it provides into both theory and practice. Pim Tuyls is a Principal Scientist at Philips Research and a Visiting Professor at the COSIC Department of the Katholieke Universiteit of Leuven, Dr Boris Skoric and Dr Tom Kevenaar are research scientists at Philips Research Laboratories, Eindhoven.
Description based upon print version of record.
Includes bibliographical references and index.
Theory of Security with Noisy Data -- Unbreakable Keys from Random Noise -- Fuzzy Commitment -- A Communication-Theoretical View on Secret Extraction -- Fuzzy Extractors -- Robust and Reusable Fuzzy Extractors -- Fuzzy Identities and Attribute-Based Encryption -- Unconditionally Secure Multiparty Computation from Noisy Resources -- Computationally Secure Authentication with Noisy Data -- Applications of Security with Noisy Data -- Privacy Enhancements for Inexact Biometric Templates -- Protection of Biometric Information -- On the Amount of Entropy in PUFs -- Entropy Estimation for Optical PUFs Based on Context-Tree Weighting Methods -- Controlled Physical Random Functions -- Experimental Hardware for Coating PUFs and Optical PUFs -- Secure Key Storage with PUFs -- Anti-Counterfeiting.
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 This comprehensive introduction offers an excellent foundation to graduate students and researchers entering the field, and will also benefit professionals needing to expand their knowledge. Readers will gain a well-rounded and broad understanding of the topic through the insight it provides into both theory and practice. Pim Tuyls is a Principal Scientist at Philips Research and a Visiting Professor at the COSIC Department of the Katholieke Universiteit of Leuven, Dr Boris Skoric and Dr Tom Kevenaar are research scientists at Philips Research Laboratories, Eindhoven.
Data encryption (Computer science).
Biometrics (Biology).
Data structures (Computer science).
Algorithms.
Cryptology.
Biometrics.
Data Structures and Information Theory.
Algorithm Analysis and Problem Complexity.