User centric privacy and security in biometrics

IET SECURITY SERIES 04 User-Centric Privacy and Security in Biometrics IET Book Series in Advances in Biometrics – Call for authors Book Series Editor: Michael Fairhurst, University of Kent, UK This Book Series provides the foundation on which to build a valuable library of reference volumes on the topic of Biometrics Iris and Periocular Biometric Recognition, Mobile Biometrics, User-centric Privacy and Security in Biometrics, and Hand-based Biometrics are the first volumes in preparation, with further titles currently being commissioned Proposals for coherently integrated, multi-author edited contributions are welcome for consideration Please email your proposal to the Book Series Editor, Professor Michael Fairhurst, at: m.c.fairhurst@kent.ac.uk, or to the IET at: author_support@theiet.org Other Titles in the Series include: Iris and Periocular Biometric Recognition (Christian Rathgeb and Christoph Busch, Eds.): Iris recognition is already widely deployed in largescale applications, achieving impressive performance More recently, periocular recognition has been used to augment biometric performance of iris in unconstrained environments where only the ocular region is present in the image This book addresses the state of the art in this important emerging area Mobile Biometrics (Guodong Guo and Harry Wechsler, Eds.): Mobile biometrics aim to achieve conventional functionality and robustness while also supporting portability and mobility, bringing greater convenience and opportunity for deployment in a wide range of operational environments However, achieving these aims brings new challenges, stimulating a new body of research in recent years, and this is the focus of this timely book Hand-based Biometric Methods and Technologies (Martin Drahanský, Ed.): This book provides a unique integrated analysis of current issues related to a wide range of hand phenomena relevant to biometrics Generally treated separately, this book brings together the latest insights into 2D/3D hand shape, fingerprints, palmprints, and vein patterns, offering a new perspective on these important biometric modalities User-Centric Privacy and Security in Biometrics Edited by Claus Vielhauer The Institution of Engineering and Technology Published by The Institution of Engineering and Technology, London, United Kingdom The Institution of Engineering and Technology is registered as a Charity in England & Wales (no 211014) and Scotland (no SC038698) © The Institution of Engineering and Technology 2018 First published 2017 This publication is copyright under the Berne Convention and the Universal Copyright Convention All rights reserved Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may be reproduced, stored or transmitted, in any form or by any means, only with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms of licences issued by the Copyright Licensing Agency Enquiries concerning reproduction outside those terms should be sent to the publisher at the undermentioned address: The Institution of Engineering and Technology Michael Faraday House Six Hills Way, Stevenage Herts, SG1 2AY, United Kingdom www.theiet.org While the authors and publisher believe that the information and guidance given in this work are correct, all parties must rely upon their own skill and judgement when making use of them Neither the authors nor publisher assumes any liability to anyone for any loss or damage caused by any error or omission in the work, whether such an error or omission is the result of negligence or any other cause Any and all such liability is disclaimed The moral rights of the authors to be identified as authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988 British Library Cataloguing in Publication Data A catalogue record for this product is available from the British Library ISBN 978-1-78561-207-7 (hardback) ISBN 978-1-78561-208-4 (PDF) Typeset in India by MPS Ltd Printed in the UK by CPI Group (UK) Ltd, Croydon Contents Preface PART I xiii Introduction and interdisciplinary approaches The interplay of privacy, security and user-determination in biometrics Claus Vielhauer 1.1 The technological view 1.2 Some societal, ethical and legal views 1.3 A taxonomical approach for discussions 1.4 Contributions of this book 1.5 Proposed reading and acknowledgements References Privacy of online handwriting biometrics related to biomedical analysis Marcos Faundez-Zanuy and Jiri Mekyska 2.1 Introduction 2.2 Online handwritten signals – an introduction 2.2.1 In-air and on-surface movements 2.3 Handwriting signals from biometrics to medical applications 2.3.1 Biometric security applications 2.3.2 Metadata applications 2.3.3 Biometric health applications 2.4 Security–health implications and concerns 2.4.1 Security where health aspects influence biometric security 2.4.2 Situations where health information can be extracted from security applications 2.4.3 Situations where the identity information must be removed 2.5 Summary and conclusions References 3 11 14 15 17 17 18 19 23 23 24 24 31 31 33 34 35 35 vi User-centric privacy and security in biometrics Privacy concepts in biometrics: lessons learned from forensics Jana Dittmann and Christian Kraetzer 3.1 Introduction: forensic science and selected privacy concepts 3.2 Privacy concepts – findings from digitised forensics of latent fingerprints 3.2.1 Sensor-acquisition-related privacy-preserving guidelines 3.2.2 Privacy-preserving-benchmarking concepts and guidelines 3.3 Privacy concepts – findings from digital forensics of face-morphing detection in face authentication systems 3.3.1 Face-morphing attacks – generalised attack procedure and privacy implications 3.3.2 Media forensic investigations and biometrics on the example of face-morphing attacks Acknowledgements References PART II Privacy and security of biometrics within general security systems 41 41 42 43 45 48 49 58 62 62 67 Physical layer security: biometrics vs physical objects Svyatoslav Voloshynovskiy, Taras Holotyak, and Maurits Diephuis 69 4.1 Introduction 4.2 Fundamentals of physical layer security based on unclonable functions 4.2.1 Randomness as a source of unclonability 4.2.2 Basic properties of unclonable functions 4.2.3 Basic enrollment-verification architecture of PUF systems 4.3 Image-PUFs: fundamentals of security with noisy data 4.3.1 Feature extraction 4.3.2 Template protection 4.3.3 Performance analysis 4.4 Attacks against biometrics and physical object protection 4.4.1 Attacks against biometric systems 4.4.2 Overview of reconstruction techniques 4.4.3 Attacks against PUFs-based systems 4.5 Main similarities and differences of biometrics and PUFs-based security 4.5.1 Summary and conclusions References 69 70 70 74 75 77 78 81 82 84 84 86 89 90 93 93 Contents Biometric systems in unsupervised environments and smart cards: conceptual advances on privacy and security Raul Sanchez-Reillo 5.1 Challenges of an unsupervised scenario 5.1.1 Presentation attacks 5.1.2 Usability 5.1.3 Personal data handling 5.2 Smart cards as secure elements 5.2.1 Internal architecture 5.2.2 Smart card operating system 5.2.3 Functionality 5.2.4 Security mechanisms 5.2.5 Other implementations 5.3 Smart cards to improve security and privacy in unsupervised biometric systems 5.3.1 Practical implementations 5.4 Conclusions References Inverse biometrics and privacy Marta Gomez-Barrero and Javier Galbally 6.1 Introduction 6.2 Synthetic biometric samples generation 6.3 Inverse biometrics methods 6.3.1 Template format 6.3.2 Similarity scores 6.3.3 Similarity score and distance function 6.3.4 Feature extraction 6.3.5 Summary 6.4 Evaluation of inverse biometrics methods 6.5 Privacy-related issues and countermeasures 6.6 Conclusions References Double-layer secret-sharing system involving privacy preserving biometric authentication Quang Nhat Tran, Song Wang, Ruchong Ou and Jiankun Hu Introduction 7.1 Conceptual clarifications 7.1.1 Steganography 7.1.2 (k, n)-Threshold secret sharing 7.1.3 Biometric template protection vii 97 98 99 100 102 103 103 105 105 107 111 113 117 118 119 123 123 124 128 130 131 132 132 133 134 138 141 143 153 153 154 154 154 156 viii User-centric privacy and security in biometrics 7.2 Related work 7.2.1 Authentication with biometric template protection 7.2.2 Secret sharing with steganography 7.3 Double-layer secret-sharing system 7.3.1 Embedding process 7.3.2 Recovery process 7.3.3 Security analysis 7.4 Experimental results 7.4.1 Settings and parameters 7.4.2 Results 7.5 Conclusion and future works References PART III 156 156 157 158 158 162 164 165 165 165 167 168 Security and privacy issues inherent to biometrics 171 Biometric template protection: state-of-the-art, issues and challenges Christian Rathgeb and Christoph Busch 173 8.1 Introduction 8.2 Biometric template protection 8.2.1 Biometric cryptosystems 8.2.2 Cancellable biometrics 8.2.3 Multi-biometric template protection 8.3 Issues and challenges 8.3.1 Performance decrease in template protection schemes 8.3.2 Data representation and feature alignment 8.3.3 Standardization and deployments 8.4 Conclusion References Handwriting biometrics – feature-based optimisation Tobias Scheidat 9.1 Introduction 9.2 Biometric feature analysis and selection 9.2.1 Wrappers 9.2.2 Filters 9.3 Reference algorithms 9.3.1 Biometric hash algorithm 9.3.2 Secure sketch algorithm 9.3.3 Handwriting-based features 9.4 Experimental evaluation 9.4.1 Methodology 9.4.2 Evaluation results 173 175 177 179 181 182 183 184 184 186 186 193 193 197 197 198 201 201 202 204 204 204 207 Contents 9.5 Conclusions and future work Acknowledgements References 10 Presentation attack detection in voice biometrics Pavel Korshunov and Sébastien Marcel 10.1 Introduction 10.1.1 Databases 10.1.2 Evaluation 10.2 Vulnerability of voice biometrics 10.3 Presentation attack detection approaches 10.3.1 Features 10.3.2 Classifiers 10.3.3 Fusion 10.4 PADs failing to generalize 10.5 Integration of PAD and ASV 10.6 Conclusions Acknowledgments References 11 Benford’s law for classification of biometric images Aamo Iorliam, Anthony T S Ho, Norman Poh, Xi Zhao and Zhe Xia 11.1 Introduction 11.2 Related work 11.2.1 Benford’s law 11.2.2 Neural networks 11.2.3 Mixed biometric data classification to preserve privacy 11.3 Experimental setup 11.3.1 Separation of different types of biometric images 11.3.2 Data sets 11.3.3 Divergence metric and separability of biometric databases 11.4 Proposed method 11.4.1 Method description 11.5 Results and discussion 11.5.1 Inter-class separability of biometric images 11.5.2 Intra-class separability of biometric images 11.5.3 Mixed inter-class and intra-class separability of biometric images 11.5.4 Comparative analysis between inter-class, intra-class and mixture of inter-class and intra-class classification of biometric images 11.6 Conclusion and future work References ix 212 213 213 217 218 219 221 222 223 225 225 226 227 231 233 234 234 237 237 238 238 242 243 244 244 244 245 248 249 250 250 252 253 254 255 255 Biometrics, identity, recognition and the private sphere [40] [41] [42] [43] [44] 399 Mesnard P, Kahan C Giorgio Agamben l’épreuve d’Auschwitz Paris: Kimé; 2001 UNESCO Information for All Programme 2007 Amit 12 Companies Leveraging Blockchain for Identification and Authentication [Online] 2016 [cited 2016 December 17] Available from: https://letstalkpayments.com/12-companies-leveraging-blockchain-foridentificationand-authentication BITNATION Bitnation Refugee Emergency Response (BRER) [Online] 2016 [cited 2016 December 17] Available from: https://refugees.bitnation.co/ Allison J Decentralised Government Project Bitnation Offers Refugees Blockchain IDs and Bitcoin Debit Cards [Online] 2016 [cited 2017 January 22] Available from: http://www.ibtimes.co.uk/decentralised-government project-bitnation-offers-refugees-blockchain-ids-bitcoindebit-cards-1526547 This page intentionally left blank Index absolute identification 380 Addenbrooke’s cognitive examination-revised (ACE-R) test 25–6 Advanced Encryption Standard (AES) 272 Advanced Multimedia and Security Lab (AMSL) 60 Agamben’s arguments 394 age detection, optical sensors for 44 Alzheimer’s disease (AD) 22, 25–6 AMBER (‘enhAnced Mobile BiomEtRics’) 11 analysis of variance 199–200 Annotated Facial Landmarks in the Wild (AFLW) database 301 anonymisation 10, 296 anonymity 49, 383 anticounterfeiting protection 71 anytime-anywhere mobile services 262 Apple’s TouchID sensors 366 Archimedes spiral and straight line 27–8 ASVspoof database 219–20, 229–30 asylum shopping 389 attack presentation classification error rate (APCER) 221–2 attacks against biometric systems 84–6 attacks against PUFs-based systems 89 authentication factor 194 authentication methods, handwriting-based 196 authentication with biometric template protection 156–7 automatic speaker verification (ASV) systems 217–19 presentation attack detection and 231–3 auto-regressive (AR) modelling 333–4, 336 auto-regressive (AR) reflection coefficients 333–4 AVspoof database 220–1, 231 behavioural biometric identifiers, de-identification of 306 gait and gesture de-identification 309–10 voice de-identification 306–9 behavioural biometrics 24, 100, 195, 306 Benford’s law 238 divergence values 238, 241, 245, 248–9 experimental setup 244 data sets 244–5 divergence metric and separability of biometric databases 245–8 separation of different types of biometric images 244 first digit probability distribution of 239 mixed biometric data classification to preserve privacy 243 neural networks 242–3 proposed method 248–50 results and discussion 250 inter-class, intra-class and mixture of inter-class and intra-class classification, comparative analysis between 254 402 User-centric privacy and security in biometrics inter-class separability of biometric images 250–2 intra-class separability of biometric images 252–3 mixed inter-class and intra-class separability of biometric images 253–4 bestEER 207–11 big data 78, 353–5 BioConvolving 181 bio-cryptosystems 156–7 BioHash 142, 156, 180–1, 197 BioID 358 biometric authentication 48, 156, 165, 173, 197, 203, 358 biometric cryptosystems 14, 175–9, 183, 273, 275–7, 362 biometric encryption 177 biometric hash algorithm 193, 195, 201–2 biometric identifier 33 behavioural 306–10 definition 297 physiological 297–306 soft 310–13 Biometric Identity Management System (BIMS) 390 biometric personal identifier 294–5 biometric-processing-on-card configuration 116 biometric salting 176, 180 biometric-system-on-card (BSoC) configuration 116 biometric template protection 156, 175, 271 biometric cryptosystems 175, 177–9, 275–7 cancellable biometrics 175, 179–81 feature transformation schemes 273–5 hybrid biometric data de-identification 277–8 issues and challenges 182 data representation and feature alignment 184 decrease in performance 183–4 standardization and deployments 184–5 multi-biometric template protection 181–2 biometric thresholding 61 biometric user authentication 194 biosignals 326, 329 bio-stego-images 158, 161–2 biotokens 180–1 Bitcoin Debit Card 395 BITNATION 395 black-box approach 297 black-hat-identity theft scheme 56 Blockchain Emergency ID 395 blockchain technology 395 block diagonal Hadamard RPs 286–7 bloom filters 180–1 blurring 271, 298 bodily privacy 294 body mass index 18–19 body silhouette de-identification 310–11 bona fide data 219 bona fide presentation classification error rate (BPCER) 221–2 camouflage-stego-images 162, 167 cancellable biometric filters 175, 180–1 cancellable biometrics 156, 175–6, 179–81, 243, 361 Canon Pixma iP4950 inkjet printer 47 Cartesian transform 275 CASIA-FACEV5 244–6 CASIA-IrisV1 245–6 centralized biometric databases 394–5 Chromatic White Light CWL600 sensor 44 classifiers 225–6 clock drawing test (CDT) 25–7 cloud infrastructures for biometrics 356–7 CloudScreen project 269 cloud service providers (CSPs) 263–4 Index cloud service users (CSUs) 263–4 cloud technologies 357–8 coarse scan 43–4 cognitive biometrics 325 electroencephalography (EEG)-based biometric recognition 327–8 experimental results 336–49 experimental setup 335–6 exploiting multiple biometric representations: information fusion 333 AR modelling 333–4 fusion strategies 334–5 MFCC modelling 334 preprocessing 329–30 protected system 331 security evaluation 333 unprotected systems 330–1 cognitive deficits 34 collision rate (CR) 204 collision reproduction rate (CRR) 204, 207, 211 commodification 391 common data protection directive complementary authentication concept computer-generated fingerprint images 46 confidentiality 295 connectivity 356 Constant Q cepstral coefficients (CQCCs) 225 contactless smart cards 107 context anomaly properties (CAP) 53 context properties (CP) 53, 59–62 ConvNet model 313 convolutional neural network (CNN) 89 correct recognition rate (CRR) 328 correlation 200 counter-forensics methods 54 cross entropy (CE) 243 cryptographic keys 156, 196, 331 cryptography 7, 264, 272 cryptosystems, biometric 362 “curse of dimension” 267, 278 403 data, defined 391 data proliferation 263 data sets, summary description of 245 Daubert standard 43, 45 dedicated files (DF) 105 deep learning networks 226 de-identification 11, 34, 44, 48, 53, 57, 265–6, 293, 296 and anonymization 296 multimodal de-identification 296–7 personal identifiers, taxonomy of 297 de-identification of behavioural biometric identifiers 306 gait and gesture de-identification 309–10 voice de-identification 306–9 de-identification of biometric data 264, 270 biometric template protection schemes 271–8 existing face image de-identification 271 Hadamard-based RP dictionaries for 284–5 de-identification of physiological biometric identifiers 297 ear de-identification 305–6 face de-identification in still images 297–301 face de-identification in videos 301–2 fingerprint de-identification 302–4 iris de-identification 304–5 de-identification of soft biometric identifiers 310 body silhouette de-identification 310–11 gender, age, race and ethnicity de-identification 312 scars, marks and tattoos (SMT) de-identification 312–13 de-identification rate 296 Delaunay triangulation 300 dementia syndrome 25 404 User-centric privacy and security in biometrics depression anxiety stress scales (DASS) questionnaire 24 detection properties (DP) 53, 59–62 DigiDak+ 44 DigiDak project 44–5 digital economy 390–1 digital synthetic samples 125 digitised dactyloscopy 42 dimension reduction 267 direct attacks 84–5 discrete cosine transform (DCT) 88, 240–1 DCT coefficients 300 DCT-II 228 discrete Fourier transform (DFT) 88 discrete wavelet transform (DWT) 88, 241, 268 distributed processing configuration 364–5 diversification 109 diversity 272, 361 double-layer secret-sharing system (DLSSS) 158 biometric authentication, involving privacy preserving 153 embedding process 158–60 bio-stego-images 161–2 camouflage-stego-images 162 cancellable template protection with Delaunay triangle-based local structure 160 experimental results results 165–7 settings and parameters 165 recovery process 162–3 recover secret image 163–4 security analysis 164–5 dragnet 295 drone-based surveillance systems, de-identification in 302 drug substances abuse and changes in handwriting 33 duplicated samples 126, 127 duress detection 31 duress finger 31 ear de-identification 305–6 e-commerce businesses 262, 265 economic migrants 386–7 EEPROM 104 eHealth and telemedicine fields 34 eigenvector-based method 298 electroencephalography (EEG)-based biometric recognition 327–8 elementary files (EF) 105 elliptic curve ciphers 264 embedding process 158–60 bio-stego-images 161–2 camouflage-stego-images 162 cancellable template protection with Delaunay triangle-based local structure 160 eMRTD 58–9, 61 entropy for biometric purpose 200 entropy studies 126 equal error rate (EER) 193, 195, 204, 207–8, 222, 328 ergonomics 101 error correction coding techniques 276 EU Council Framework Decision 2008/977/JHA 42 EU Data Protection Reform 42 EURODAC regulation 389–90 EU’s Data Protection Directive (95/46/EC) 34 evolution of biometric systems 359 enabling advanced privacy 359–62 Indian Unique ID (UID) project 362 multimodal authentication, accuracy of 363 multimodal processing algorithms, optimization of 363–4 system design that ensures high availability of resources 364–5 system scalability 364 ubiquitous biometrics 362 expansion factor 203 external authentication 109 eyes-closed (EC) conditions 328 eyes-open (EO) scenario 328 Index face biometrics 267–9 Facebook 368 face de-identification 49, 271 in still images 297–301 in videos 301–2 face-image-based authentication token 50 face image de-identification 271 face-morphing attacks 48–62 face recognition 4, 217, 267–8 face-verification system 203 Facial Identity Preserving (FIP) features 300 fair information practice principles 10 false acceptance rate (FAR) 328, 337 false match rate (FMR) 135, 204 false non-match rate (FNMR) 135, 204 false rejection rate (FRR) 303, 328, 337 “false” refugees 388 Faraday jail 108 fast Fourier transform (FFT) 228 feature extraction techniques 78–81, 132–3, 266 feature selection/analysis 196 feature sets 18 feature transformation schemes 175, 273–5 feature vector 79, 81–2, 203, 286 Fertile Crescent 381, 391 filters 198 analysis of variance 199–200 correlation 200 entropy 200 FindFace 368 fine scan 43 fingerprint data set 245 fingerprint de-identification 302–4 fingerprint images 244–5, 303 fingerprint recognition algorithms 358, 363 Fingertec 31 first digit law 13 Fisher discriminant analysis-based face templates 273 Folstein test 25 405 forensic science and privacy concepts 41–2 findings from digital forensics of face-morphing detection in face authentication systems 48 generalised attack procedure and privacy implications 49–58 media forensic investigations and biometrics 58–62 findings from digitised forensics of latent fingerprints 42 privacy-preserving-benchmarking concepts and guidelines 45–8 sensor-acquisition-related privacy-preserving guidelines 43–5 frequency transforms 268 fusion 226–7 fusion strategies 334–5 fuzzy commitment schemes (FCS) 177, 276, 331 fuzzy extractor 176, 196, 202 fuzzy vault scheme 178, 276–7 FVC2000 244–5 gait and gesture de-identification 309–10 GALILEO BE Light amplifier 335 Gauss-functions 197 Gaussian blurring 310 Gaussian filters 271, 298 Gaussian mixture models 24, 270, 276, 307 gender, age, race and ethnicity de-identification 312 gender recognition 24 Generalised Benford’s law 239 generators 279 geometrical reranking 80 geometric transforms 181 gestures 310 GivenPIN 195 global mobility of people 386 difficult challenges 387–9 406 User-centric privacy and security in biometrics providing refugees with biometric identifiers 389–90 global travellers 387 Gram–Schmidt orthonormalisation (GSO) algorithm 280 graphical tablets 30 H2020 CloudScreen EU-project 269 Haar wavelet decomposition 269 Hadamard matrices, construction of 282–4 half-total error rate (HTER) 328 hand-crafted feature design 79–80 hand gesture de-identification 310 hand-gesture recognition 310 handwriting biometrics 193 experimental evaluation 204 evaluation results 207–12 methodology 204–7 filters 198 analysis of variance 199–200 correlation 200 entropy 200 future work 212–13 reference algorithms 201 biometric hash algorithm 201–2 handwriting-based features 204 secure sketch algorithm 202–4 wrappers 197–8 handwriting-verification system 196 healthcare services 260, 263 helper data 175–7, 275–6 hidden Markov model 196, 308 hill-climbing algorithm 131 histogram of oriented gradients (HOG) 89 homomorphic encryption 10, 272 house drawing copy 27 human biometrics as security features 70 human security 69–70 hybrid biometric data de-identification 277–8 HYPR 358 IAD systems 304 ICA (independent component analysis) 182 ICT landscape for biometric systems 355 cloud infrastructures for biometrics 356–7 Internet of Things (IoT) 355–6 ID-based cryptography 265 identification, defined 380 identifiers 33, 296–7 identity, identification, recognition 379–81 identity revolution 386 image-PUF enrollment and verification 77 feature extraction 78–81 first practical challenge 77–8 performance analysis 82–4 authentication stage 82 goal of the defender 84 identification stage 83 probability of miss and probability of successful attack 82 second practical challenge 78 template protection 81–2 impostor attack presentation match rate (IAPMR) 221 in-air and on-surface movements 19–22 Indian Aadhaar Biometric Identification Program 390 Indian Unique ID (UID) project 6, 138, 362 multimodal authentication, accuracy of 363 multimodal processing algorithms, optimization of 363–4 system design that ensures high availability of resources 364–5 system scalability 364 indirect attacks 85–6 information privacy 294 information technology (IT) security informed consent attempts 10 innovations, breaking 18 Index Instagram 368 integer partition problem 286–7 integer variables (Bsize, Htype,T) 284–5 integrated circuit cards (ICCs) 103 inter-class entropy 200 inter face device (IFD) 106 internal authentication 108–9 Internet 259, 261, 265 Internet of Things (IoT) 260, 264, 354, 355–6 interoperability 356 interplay of privacy, security and user-determination in biometrics societal, ethical and legal views 6–7 taxonomical approach for discussions 7–11 technological view 3–6 intersession variability (ISV) 219 interval matrix 201–2 intra-class entropy 200 intuition 195 inverse biometrics and privacy 123, 128 evaluation of 134–8 feature extraction 132–3 privacy-related issues and countermeasures 138–41 similarity scores 131–2 similarity score and distance function 132 synthetic biometric samples generation 124–8 template format 130 inverted mel-scale frequency cepstral coefficients (IMFCC) 227 invertible transformation-based protection schemes 273–5 iris de-identification 304–5 iris-recognition algorithms 131–2 irreversibility 126, 140, 295 i-vectors 219, 222–3 Java Card 105, 115, 117 JPEG coefficients 238, 245, 247 407 (k, n)-threshold secret sharing 154–5, 157 kal-diphone 274 k-anonymity framework 271 Karhunen–Loeve transform 267 KAZE 79 key-binding schemes 176 Keyence VK-x110 series confocal laser scanning microscope 47 key-generation schemes 176 knowledge signatures 181 known attacks 219, 225–6 Kronecker product 282 k-Same algorithm 298–9 k-Same-Select 298–9 Labeled Faces in the Wild (LFW) dataset 301 lifestyle intelligence 370 linear frequency cepstral coefficients (LFCC) 227 Line Integral Convolution (LIC) 309 linkability potential 368 LinkedIn 368 local binary patterns (LBP) face features 272, 277, 314 logical access (LA) attacks 219–20 logical security mechanism 108 logistic regression (LR) classifier 226 machine learning feature principles 79–80 match-on-card (MoC) applications 115, 142 media forensic investigations and biometrics 58–62 media forensic traces 59–60 mel-frequency cepstrum coefficients (MFCCs) 231, 333–4 metadata, defined 24 metadata analysis 23 metadata aware architecture 359, 361 micro-SIM 112 408 User-centric privacy and security in biometrics mini-mental state examination (MMSE) 25–6 mixed biometrics 238, 254 mobile biometry (MOBIO) database 223 mobile computing 357 mobility 356, 386 Model-based k-Same algorithms 298 Modern Era 383 monozygotic twins 380 morphing 127 morph quality assurance (QA) 52 multi-biometric template protection 181–2 multidisciplinary analysis of implementation of biometric systems 353 evolution of biometric systems 359 enabling advanced privacy 359–62 Indian Unique ID (UID) project 362–5 ubiquitous biometrics 362 ICT landscape for biometric systems 355 cloud infrastructures for biometrics 356–7 Internet of Things (IoT) 355–6 new implementation potential 357–9 societal implications 365 biometric data collection 366 concerns 370–1 secondary uses of biometric data 369–70 social media, biometrics in 367–9 multi-layer perceptrons (MLP) 242 multimodal authentication, accuracy of 363 multimodal de-identification 296–7 multimodal processing algorithms, optimization of 363–4 multiple biometric representations, exploiting 333 auto-regressive (AR) modelling 333–4 fusion strategies 334–5 mel-frequency cepstrum coefficient (MFCC) modelling 334 mutual authentication 109 Naive methods of face de-identification 297–8 nano-SIM 112 Nation-States 383–4 Nelder–Mead simplex algorithm 130, 132 Neolithic Revolution 381 neural networks (NN) 238, 242–3 1951 Convention 388, 390 non-biometric identifiers 297 non-homomorphic cryptographic algorithms 272 non-invertible geometric transforms 179 non-invertible transformation biometric template protection schemes 275 Normalized Pixel Difference (NPD) features 295, 301 numerical identity 380 offline handwriting authentication 194 on-card biometric comparison 115, 117 online handwriting biometrics, privacy of 17, 194 in-air and on-surface movements 19–22 medical applications 23 health applications 24–30 metadata applications 24 security applications 23 security–health implications and concerns 31 security where health aspects influence the biometric security 31–3 situations where health information can be extracted from security applications 34 Index situations where the identity information must be removed 34 orientated fast and rotated brief (ORB) 79 Orthogonal group 279 overlapped circles (ellipses) 28–9 parametric biometric systems testing 125 Parkinsonian (PD) handwriting 30 Parkinson’s disease (PD) 22, 25, 28, 30 dysgraphia 30 parrot recognition 298 password hardening 179 Pearson correlation coefficient 200 Pentagon test 26 perceptual quality 60–1 personal data handling 102–3 personal identifiers, taxonomy of 297 personal recognition through human history 381–5 personal space 392 photo-ID documents, attacks on 50–2 physical access (PA) 218 physical layer security 69 attacks against biometric systems 84–6 attacks against PUFs-based systems 89 based on unclonable functions 70 basic properties of unclonable functions 74 enrollment-verification architecture of PUF systems 75–7 randomness as a source of unclonability 70–4 extrinsic features 70 image-PUFs 77 feature extraction 78–81 performance analysis 82–4 template protection 81–2 intrinsic features 70 reconstruction techniques 86–9 409 similarities and differences of biometrics and PUFs-based security 90–3 physical object security 69, 76 physical unclonable functions (PUF) 70–1 enrollment-verification architecture of 75–7 generalized deployment of 72 multichallenge principle 76 properties of 75 PUFs-based security and biometrics similarities and differences of 90–3 physiological biometric identifiers, de-identification of 297–306 picture-to-identity linking 369 PINs and passwords 108, 112 Pinterest 368 pixelation 297–8 plug-in card 112 point of service (PoS) 102 polynomial logistic regression (PLR) 226 potential vulnerable points (PVPs) 114 Precise Biometrics 117 preprocessing 329–30 presentation attack detection (PAD) 100, 141, 217 and ASV, integration of 231–3 databases 219 ASVspoof database 219–20 AVspoof database 220–1 evaluation 221–2 failing to generalize 227–31 presentation attack detection approaches 223–5 classifiers 225–6 fusion 226–7 vulnerability of voice biometrics 222–3 presentation attacks 13, 48–9, 85, 99–100 principal component analysis (PCA) 182, 267–8 410 User-centric privacy and security in biometrics privacy, defined 293 privacy, person and human dignity 391–6 privacy by design and by default, concept of privacy-conformtest sets 47 privacy-enhancing technologies (PET) 8, 10 privacy of communications 294 privacy-preserving-benchmarking concepts and guidelines 45–8 privacy-preserving testing 43 privacy protection strategy 264–5 privacy-related issues and countermeasures 138–41 private template scheme 177 protected system 331–3 security evaluation 333 pseudo-identities generation 126 Pseudonym 195 pseudonymous identifier (PI) encoder 174 public key infrastructure (PKI) 111, 117, 260 PUT vein database 245 qualitative identity 380 qualities 379–80 quality factors (QFs) 240 quantization schemes 178 radio-frequency identification (RFID) 50, 70 RAM memory 104 random multispace quantisation technique 273 random orthonormal projections (ROPs) 278 random permutations 180 random projections (RPs) 179–80, 259, 278 analytical notes on the performance and security of block diagonal Hadamard RP 286–7 de-identification of biometric data 270 biometric template protection schemes 271–8 existing face image de-identification 271 Hadamard-based RP dictionaries for 284–5 dual role of biometrics in privacy protection 265 face biometrics 267–9 speaker recognition 269–70 evolution of privacy threats 261 post-cloud privacy 263–4 pre-cloud privacy 261–3 towards a privacy protection strategy 264–5 Hadamard matrices, construction of 282 Sylvester-type Hadamard matrices (SH) 282–3 Walsh Hadamard matrices (W) 283–4 Walsh–Paley matrices (WP) 283 RP generation schemes 279 alternative scheme for RP generation 280–1 Gram–Schmidt orthonormalisation (GSO) algorithm 280 real samples, combination of 126 reconstruction techniques 86–9 based on machine-learning approach 88–9 signal processing reconstruction 87–8 recovery process 162–3 recover secret image 163–4 rectangular frequency cepstral coefficients (RFCC) 227 reference algorithms 201 biometric hash algorithm 201–2 handwriting-based features 204 secure sketch algorithm 202–4 refugees, providing with biometric identifiers 389–90 Index refugees and displaced people 387 regions of interest (ROIs), de-identification of 301 reproduction rate (RR) 204 repurposing 369 RESTFul architectures 358 revocability 272–3 Rey–Osterrieth complex figure test 28 right to privacy legislation 261 Rivest–Shamir–Adleman (RSA) 264 Roman Empire 383 ROM memory 104 salting 181, 273–5 sample point sequence (SPS) 194, 201 scale-invariant feature transform (SIFT) 79, 89, 312 scars, marks and tattoos (SMT) de-identification 312–13 SecretPIN 195 secret sharing with steganography 157 secure messaging (SM) 110–11 secure sketch algorithm 193, 197, 202–4 Secure Socket Layer (SSL) 260 security aid module (SAM) module 103, 111 security analysis 164–5 security by design 143 sensor-acquisition-related privacy-preserving guidelines 43–6 sensor precision 381 sequential backward selection (sbs) 198 sequential forward selection (sfs) 198 Service Oriented Applications (SoAP) 358 Service Oriented Architectures (SoA) 357–8 session keys (SKs) 110 SFinGe 46 shared key authentication 108 shielding functions 179 short-term FFT analysis 270 signal processing reconstruction 87–8 411 significant eigenfaces 268 similarity scores 131–2 simple wrapper (simple) 198 singular value decomposition (SVD) 79 SmartBorders package 138 smart cards 97, 103 functionality 105–7 to improve security and privacy in unsupervised biometric systems 113–17 internal architecture 103–4 practical implementations 117–18 security mechanisms 107–11 smart card operating system (SCOS) 105 unsupervised environments and 97 social media, biometrics in 362, 367–9 social networks 54, 217, 260 aggregation soft biometric identifiers 297 de-identification of 310–13 Soft Biometrics 23–4, 367 soft biometrics, extraction of 368 Spanish National ID Card (DNIe) 117–18 sparsity-based methods 87 speaker recognition 269–70 speeded up robust features (SURF) 79 spiral and straight lines test 29 squared error (SE) 243 squares due to error (SSE) 240 standards compliance 59 steganography 153–4, 272 secret sharing with 157 StirMark tool 47 StirTrace tool 44, 47 store-on-card 114 configuration 115 stress, detection of 31 subband centroid frequency coefficient (SCFC) 227–8 subband centroid magnitude coefficient (SCMC) 228 subband spectral flux coefficients (SSFC) 227 412 User-centric privacy and security in biometrics subscriber identification module (SIM) 103 supervised environment 99 assisted scenario 98 controlled scenario 98 observed scenario 98 private scenario 98 visible scenario 98 support vector machines 24 Suprema 31 Sylvester-type Hadamard matrices (SH) 282–3 Symbol (semantic) 195 synthesis model 87 synthetic biometric samples generation 124–8 synthetic individuals 127 system-related metadata 24 system security tactile screens 18 tattoos 312, 382 de-identification 313 template, defined 303 template matching for speech-dependent recognition 270 territorial privacy 294 text-independent voice conversion 307 threat vectors 4–6 THRIVE system for enrolment and authentication protocols 272 Titanic phenomenon 295 TouchID sensors 366 transformation-based biometric cryptosystems 287–8 transform learning model 87 transparency enhancing tools (TETs) 10 “true” refugees 388 trusted third party (TTP) 158, 164–5 turbo encoding process 331 ubiquitous biometrics 362 undetectability 154 Universal Background Model (UBM) 223, 270, 276 unknown attacks 219, 225–6 unlinkability 175, 295 unprotected systems 330–1 unsupervised scenarios 97–8 challenges of 98 personal data handling 102–3 presentation attacks 99–100 usability 100–2 USB tokens 112–13 user-centric aspects in biometrics user stress, detection of 31 VGGNet 313 Visual-evoked potentials 328 Viterbi path approach 196 Voice Convergin tool 274 voice-conversion algorithm 220 voice-conversion methods 307 voice de-identification 306–9 voice transformation (VT) 274–5, 306 Voronoi neighbour structures (VNSs) 157 vulnerability and irreversibility studies 126 Walsh Hadamard matrices (W) 283–4 Walsh–Paley matrices (WP) 283 Web technology 259, 261 WEKA’s Bagging classifier 241 Western civilization 377–8 Where (semantic) 195 white hat de-identification scenario 57 “within-biometrics” perspective work-sharing 115 wrappers 197–8 zero-impostors 219 ... biometrics in presence of other emerging trends in IT technology By suggesting another very interesting line of thinking in this chapter, the potential to use biometrics for cross-linking and information... chapter, Faundez-Zanuy and Mekyska present interesting insights in the link between biometrics, privacy and medical analysis on the example of handwriting in their chapter ‘Online handwritten analysis... security in biometrics Privacy and security of biometrics As part of general security systems Issues inherent to biometrics User-centricity and user-determination Figure 1.1 Three main aspects of privacy