Tuyls / Skoric / Kevenaar Security with Noisy Data

On Private Biometrics, Secure Key Storage and Anti-Counterfeiting
1. Auflage 2007
ISBN: 978-1-84628-984-2
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 340 Seiten

Noisy data appear very naturally in applications where the authentication is based on physical identifiers. This book provides a self-contained overview of the techniques and applications of security based on noisy data. It provides a comprehensive overview of the theory of extracting cryptographic keys from noisy data, and describes applications in the field of biometrics, secure key storage, and anti-counterfeiting.

Autoren/Hrsg.

Tuyls, Pim

Skoric, Boris

Kevenaar, Tom

#koric, Boris

Inhaltsverzeichnis

1;Foreword;5
2;Acknowledgments;8
3;Contents;9
4;Contributors;11
5;1 Introduction;14
5.1;1.1 An Introduction to Security with Noisy Data;14
5.2;1.2 An Introduction to Biometrics;18
5.3;1.3 An Introduction to Physical Unclonable Functions;22
5.4;1.4 Overview of the Book;27
6;Theory of Security with Noisy Data;31
6.1;2 Unbreakable Keys from Random Noise;32
6.1.1;2.1 Information-Theoretic Cryptographic Security;32
6.1.2;2.2 Smooth Renyi Entropies;37
6.1.3;2.3 Information-Theoretic Reductions;38
6.1.4;2.4 Turning Correlated Randomness into Keys;45
6.1.5;2.5 Secrecy from Completely Insecure Communication;53
6.2;3 Fuzzy Commitment;56
6.2.1;3.1 Introduction;56
6.2.2;3.2 A Description of Fuzzy Commitment;56
6.2.3;3.3 Biometrics;60
6.2.4;3.4 Knowledge-Based Authentication;64
6.2.5;3.5 Beyond Fuzzy Commitment;66
6.3;4 A Communication-Theoretical View on Secret Extraction;68
6.3.1;4.1 Introduction;68
6.3.2;4.2 Preliminaries;69
6.3.3;4.3 Model: Biometrics as Random Codewords;70
6.3.4;4.4 Identification Capacity;72
6.3.5;4.5 Proof Outline for Theorem 4.1;73
6.3.6;4.6 Hypothesis Testing; Maximum Likelihood;77
6.3.7;4.7 Private Templates;78
6.3.8;4.8 Secrecy and Identification Capacity;84
6.3.9;4.9 Relation with Fuzzy Extractors;87
6.3.10;4.10 Conclusion;88
6.4;5 Fuzzy Extractors;89
6.4.1;5.1 Motivation;89
6.4.2;5.2 Basic Definitions;91
6.4.3;5.3 Basic Constructions;94
6.4.4;5.4 Improving Error-Tolerance via Relaxed Notions of Correctness;100
6.4.5;5.5 Strong Privacy Guarantees;102
6.4.6;5.6 Robustness and Protection Against Active Attacks;106
6.5;6 Robust and Reusable Fuzzy Extractors;110
6.5.1;6.1 Introduction;110
6.5.2;6.2 Background and Definitions;113
6.5.3;6.3 Flexible Error Models;114
6.5.4;6.4 Practical Robustness;115
6.5.5;6.5 Toward Reusability;119
6.5.6;6.6 Summary;121
6.6;7 Fuzzy Identities and Attribute-Based Encryption;122
6.6.1;7.1 Introduction;122
6.6.2;7.2 Preliminaries;126
6.6.3;7.3 Other Approaches;128
6.6.4;7.4 Our Construction;128
6.6.5;7.5 Large-Universe Construction;131
6.6.6;7.6 Conclusions;133
6.6.7;7.7 Applications Beyond Biometrics;134
6.7;8 Unconditionally Secure Multiparty Computation from Noisy Resources;135
6.7.1;8.1 Introduction;135
6.7.2;8.2 Preliminaries;138
6.7.3;8.3 Monotones;141
6.7.4;8.4 Bit Commitment from Noise;142
6.7.5;8.5 Oblivious Transfer from Noise;143
6.7.6;8.6 Pseudo-Signatures and Broadcast from Noise;145
6.7.7;8.7 More Realistic Models;146
6.8;9 Computationally Secure Authentication with Noisy Data;148
6.8.1;9.1 Introduction;148
6.8.2;9.2 Exact Secure Matching;150
6.8.3;9.3 Approximate Secure Matching;154
6.8.4;9.4 Conclusion;156
7;Applications of Security with Noisy Data;157
7.1;10 Privacy Enhancements for Inexact Biometric Templates;158
7.1.1;10.1 Introduction;158
7.1.2;10.2 Related Work;159
7.1.3;10.3 Hashing or Encrypting Biometric Data;162
7.1.4;10.4 Cancelable Biometrics;166
7.1.5;10.5 Discussion;172
7.2;11 Protection of Biometric Information;174
7.2.1;11.1 Introduction;174
7.2.2;11.2 Privacy Threats of Biometrics;179
7.2.3;11.3 Requirements for Template Protection;180
7.2.4;11.4 An Architecture for Biometric Template Protection;182
7.2.5;11.5 Quantization of Biometric Measurements;184
7.2.6;11.6 Security and Privacy Considerations;191
7.2.7;11.7 Application Examples of Template-Protected Biometric Systems;193
7.2.8;11.8 Conclusions;198
7.3;12 On the Amount of Entropy in PUFs;199
7.3.1;12.1 Introduction;199
7.3.2;12.2 Information-Theoretic Framework;201
7.3.3;12.3 Information Theory of Optical PUFs;204
7.3.4;12.4 Information Theory of Coating PUFs;209
7.4;13 Entropy Estimation for Optical PUFs Based on Context- Tree Weighting Methods;220
7.4.1;13.1 Generating a Shared Secret Key;220
7.4.2;13.2 Physical Unclonable Functions;222
7.4.3;13.3 Entropy of a Two-Dimensional Stationary Process;222
7.4.4;13.4 Conditional Entropy of a Two-Dimensional Stationary Process Given a Second One;225
7.4.5;13.5 Mutual Information Estimation: Convergence;227
7.4.6;13.6 The Maurer Scheme in the Ergodic Case;228
7.4.7;13.7 Context-Tree Weighting Methods;228
7.4.8;13.8 Analysis of Speckle Patterns;230
7.4.9;13.9 Conclusions;235
7.5;14 Controlled Physical Random Functions;237
7.5.1;14.1 Introduction;237
7.5.2;14.2 CPUF Primitives;243
7.5.3;14.3 Challenge Response Pair Management;249
7.5.4;14.4 Certified Execution;253
7.5.5;14.5 Conclusion;254
7.6;15 Experimental Hardware for Coating PUFs and Optical PUFs;256
7.6.1;15.1 Introduction;256
7.6.2;15.2 Coating PUF Test ICs;257
7.6.3;15.3 Bare Optical PUFs;265
7.6.4;15.4 Integrated Optical PUF;267
7.7;16 Secure Key Storage with PUFs;270
7.7.1;16.1 Introduction;270
7.7.2;16.2 PUFs for Read-Proof Hardware;273
7.7.3;16.3 Cryptographic Preliminaries;276
7.7.4;16.4 Secure Key Storage with Optical PUFs;278
7.7.5;16.5 Key Extraction from Speckle Patterns;279
7.7.6;16.6 Secure Key Storage with Coating PUFs;284
7.8;17 Anti-Counterfeiting;294
7.8.1;17.1 Introduction;294
7.8.2;17.2 Model;297
7.8.3;17.3 Unclonable RFID Tags;300
7.8.4;17.4 Secure Identification Protocols;306
7.8.5;17.5 ECC Implementations for RFID;306
7.8.6;17.6 Results and discussion;311
8;References;314
9;Index;333