Reversing the irreversible: A survey on inverse biometrics

Abstract With the widespread use of biometric recognition, several issues related to the privacy and security provided by this technology have been recently raised and analysed. As a result, the early common belief among the biometrics community of templates irreversibility has been proven wrong. It is now an accepted fact that it is possible to reconstruct from an unprotected template a synthetic sample that matches the bona fide one. This reverse engineering process, commonly referred to as inverse biometrics, constitutes a severe threat for biometric systems from two different angles: on the one hand, sensitive personal data (i.e., biometric data) can be derived from compromised unprotected templates; on the other hand, other powerful attacks can be launched building upon these reconstructed samples. Given its important implications, biometric stakeholders have produced over the last fifteen years numerous works analysing the different aspects related to inverse biometrics: development of reconstruction algorithms for different characteristics; proposal of methodologies to assess the vulnerabilities of biometric systems to the aforementioned algorithms; development of countermeasures to reduce the possible effects of attacks. The present article is an effort to condense all this information in one comprehensive review of: the problem itself, the evaluation of the problem, and the mitigation of the problem. The present article is an effort to condense all this information in one comprehensive review of: the problem itself, the evaluation of the problem, and the mitigation of the problem.

[1]  Svetlana Yanushkevich,et al.  Biometric Inverse Problems , 2005 .

[2]  Christoph Busch,et al.  Unit-Selection Attack Detection Based on Unfiltered Frequency-Domain Features , 2016, INTERSPEECH.

[3]  Frans M. J. Willems,et al.  Biometric Systems: Privacy and Secrecy Aspects , 2009, IEEE Transactions on Information Forensics and Security.

[4]  Pong C. Yuen,et al.  On the Reconstruction of Face Images from Deep Face Templates , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Gérard D. Cohen,et al.  Optimal Iris Fuzzy Sketches , 2007, 2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems.

[6]  Satoshi Nakamura,et al.  Voice conversion through vector quantization , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

[7]  Rama Chellappa,et al.  Cancelable Biometrics: A review , 2015, IEEE Signal Processing Magazine.

[8]  Erik Reinhard,et al.  An Ocularist's Approach to Human Iris Synthesis , 2003, IEEE Computer Graphics and Applications.

[9]  K.W. Bowyer,et al.  The Best Bits in an Iris Code , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Miguel Angel Ferrer-Ballester,et al.  A novel hand reconstruction approach and its application to vulnerability assessment , 2014, Inf. Sci..

[11]  Richa Singh,et al.  Synthetic iris presentation attack using iDCGAN , 2017, 2017 IEEE International Joint Conference on Biometrics (IJCB).

[12]  Arun Ross,et al.  From Template to Image: Reconstructing Fingerprints from Minutiae Points , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  A. Stoianov,et al.  Security issues of Biometric Encryption , 2009, 2009 IEEE Toronto International Conference Science and Technology for Humanity (TIC-STH).

[14]  Max Welling,et al.  Auto-Encoding Variational Bayes , 2013, ICLR.

[15]  Edmond Locard,et al.  Finger-Prints Can Be Forged , 1927 .

[16]  Andrew Chi-Chih Yao,et al.  How to generate and exchange secrets , 1986, 27th Annual Symposium on Foundations of Computer Science (sfcs 1986).

[17]  Claus Vielhauer,et al.  Reverse-engineer methods on a biometric hash algorithm for dynamic handwriting , 2010, MM&Sec '10.

[18]  Enrique Argones-Rúa,et al.  Biometric Template Protection Using Universal Background Models: An Application to Online Signature , 2012, IEEE Transactions on Information Forensics and Security.

[19]  Marta Gomez-Barrero,et al.  General Framework to Evaluate Unlinkability in Biometric Template Protection Systems , 2018, IEEE Transactions on Information Forensics and Security.

[20]  Miguel Angel Ferrer-Ballester,et al.  On-line signature recognition through the combination of real dynamic data and synthetically generated static data , 2015, Pattern Recognit..

[21]  A. Adler,et al.  Images can be regenerated from quantized biometric match score data , 2004, Canadian Conference on Electrical and Computer Engineering 2004 (IEEE Cat. No.04CH37513).

[22]  Chang Liu,et al.  Study on Synthetic Face Database for Performance Evaluation , 2006, ICB.

[23]  Jin Hyung Kim,et al.  Generation of handwritten characters with Bayesian network based on-line handwriting recognizers , 2003, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings..

[24]  Madhu Sudan,et al.  A Fuzzy Vault Scheme , 2006, Des. Codes Cryptogr..

[25]  Minoru Mori,et al.  GENERATING NEW SAMPLES FROM HANDWRITTEN NUMERALS BASED ON POINT CORRESPONDENCE , 2004 .

[26]  Julian Fiérrez,et al.  Variable-length template protection based on homomorphic encryption with application to signature biometrics , 2016, 2016 4th International Conference on Biometrics and Forensics (IWBF).

[27]  Réjean Plamondon,et al.  The generation of handwriting with delta-lognormal synergies , 1998, Biological Cybernetics.

[28]  Sudeep Sarkar,et al.  From Scores to Face Templates: A Model-Based Approach , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[29]  Alessandro Neri,et al.  Template protection for HMM-based on-line signature authentication , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[30]  Andreas Uhl,et al.  Statistical attack against iris-biometric fuzzy commitment schemes , 2011, CVPR 2011 WORKSHOPS.

[31]  Ee-Chien Chang,et al.  Finding the original point set hidden among chaff , 2006, ASIACCS '06.

[32]  Réjean Plamondon,et al.  Synthetic on-line signature generation. Part I: Methodology and algorithms , 2012, Pattern Recognit..

[33]  Andrew Beng Jin Teoh,et al.  Biophasor: Token Supplemented Cancellable Biometrics , 2006, 2006 9th International Conference on Control, Automation, Robotics and Vision.

[34]  Arun Ross,et al.  Biometrics Security and Privacy Protection [From the Guest Editors] , 2015, IEEE Signal Process. Mag..

[35]  Rama Chellappa,et al.  Continuous User Authentication on Mobile Devices: Recent progress and remaining challenges , 2016, IEEE Signal Processing Magazine.

[36]  Thomas Vetter,et al.  A morphable model for the synthesis of 3D faces , 1999, SIGGRAPH.

[37]  Tomoki Toda,et al.  The Voice Conversion Challenge 2016 , 2016, INTERSPEECH.

[38]  Benny Pinkas,et al.  SCiFI - A System for Secure Face Identification , 2010, 2010 IEEE Symposium on Security and Privacy.

[39]  Julien Bringer,et al.  The best of both worlds: Applying secure sketches to cancelable biometrics , 2008, Sci. Comput. Program..

[40]  S. P. Lloyd,et al.  Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.

[41]  Davide Maltoni Generation of Synthetic Fingerprint Image Databases , 2004 .

[42]  Satoshi Nakamura,et al.  Lip movement synthesis from speech based on hidden Markov models , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[43]  Shantanu Rane,et al.  Standardization of Biometric Template Protection , 2014, IEEE MultiMedia.

[44]  Tal Hassner,et al.  Do We Really Need to Collect Millions of Faces for Effective Face Recognition? , 2016, ECCV.

[45]  Hakil Kim,et al.  Reconstruction of Fingerprints from Minutiae Using Conditional Adversarial Networks , 2018, IWDW.

[46]  Andreas Uhl,et al.  A survey on biometric cryptosystems and cancelable biometrics , 2011, EURASIP J. Inf. Secur..

[47]  Julian Fiérrez,et al.  Cancelable Templates for Sequence-Based Biometrics with Application to On-line Signature Recognition , 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[48]  Jana Dittmann,et al.  Handwriting Biometric Hash Attack: A Genetic Algorithm with User Interaction for Raw Data Reconstruction , 2010, Communications and Multimedia Security.

[49]  Frédéric Jurie,et al.  Reconstructing faces from their signatures using RBF regression , 2013, BMVC.

[50]  Issa Traoré,et al.  Inverse Biometrics for mouse Dynamics , 2008, Int. J. Pattern Recognit. Artif. Intell..

[51]  Martin Wattenberg,et al.  A fuzzy commitment scheme , 1999, CCS '99.

[52]  Vincenzo Piuri,et al.  A privacy-compliant fingerprint recognition system based on homomorphic encryption and Fingercode templates , 2010, 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[53]  Vincenzo Piuri,et al.  Implementing FingerCode-based identity matching in the encrypted domain , 2010, 2010 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications.

[54]  Sébastien Marcel,et al.  On the vulnerability of face verification systems to hill-climbing attacks , 2010, Pattern Recognit..

[55]  Kiran B. Raja,et al.  On the vulnerability of face recognition systems towards morphed face attacks , 2017, 2017 5th International Workshop on Biometrics and Forensics (IWBF).

[56]  Anil K. Jain,et al.  Handbook of Fingerprint Recognition , 2005, Springer Professional Computing.

[57]  Alessandra Lumini,et al.  Fake fingertip generation from a minutiae template , 2008, 2008 19th International Conference on Pattern Recognition.

[58]  Guy Gogniat,et al.  Recent Advances in Homomorphic Encryption: A Possible Future for Signal Processing in the Encrypted Domain , 2013, IEEE Signal Processing Magazine.

[59]  Sharath Pankanti,et al.  On the Individuality of Fingerprints , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[60]  Arun Ross,et al.  Generating Synthetic Irises by Feature Agglomeration , 2006, 2006 International Conference on Image Processing.

[61]  Tieniu Tan,et al.  An iris image synthesis method based on PCA and super-resolution , 2004, ICPR 2004.

[62]  Koray Kavukcuoglu,et al.  Pixel Recurrent Neural Networks , 2016, ICML.

[63]  Frans M. J. Willems,et al.  Information Leakage in Fuzzy Commitment Schemes , 2010, IEEE Transactions on Information Forensics and Security.

[64]  Alessandra Lumini,et al.  Fingerprint Image Reconstruction from Standard Templates , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[65]  C. Busch,et al.  Multi-algorithm fusion with template protection , 2009, 2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems.

[66]  Guy Gogniat,et al.  Recent Advances in Homomorphic Encryption , 2013 .

[67]  Fabio Roli,et al.  Adversarial Biometric Recognition : A review on biometric system security from the adversarial machine-learning perspective , 2015, IEEE Signal Processing Magazine.

[68]  Steven Furnell,et al.  Surveying the Development of Biometric User Authentication on Mobile Phones , 2015, IEEE Communications Surveys & Tutorials.

[69]  Venu Govindaraju,et al.  Advances in Biometrics: Sensors, Algorithms and Systems , 2007 .

[70]  Nicholas W. D. Evans,et al.  On the vulnerability of automatic speaker recognition to spoofing attacks with artificial signals , 2012, 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO).

[71]  Marios Savvides,et al.  How to Generate Spoofed Irises From an Iris Code Template , 2011, IEEE Transactions on Information Forensics and Security.

[72]  Anil K. Jain,et al.  Multibiometric Cryptosystems Based on Feature-Level Fusion , 2012, IEEE Transactions on Information Forensics and Security.

[73]  John D. Bustard The Impact of EU Privacy Legislation on Biometric System Deployment: Protecting citizens but constraining applications , 2015, IEEE Signal Processing Magazine.

[74]  Anil K. Jain,et al.  Bridging the gap: from biometrics to forensics , 2015, Philosophical Transactions of the Royal Society B: Biological Sciences.

[75]  Xueyin Lin,et al.  Realistic mouth synthesis based on shape appearance dependence mapping , 2002, Pattern Recognit. Lett..

[76]  Yannis Stylianou,et al.  Voice Transformation: A survey , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[77]  Marina Blanton,et al.  Secure and Efficient Protocols for Iris and Fingerprint Identification , 2011, ESORICS.

[78]  Alex ChiChung Kot,et al.  Fingerprint Combination for Privacy Protection , 2013, IEEE Transactions on Information Forensics and Security.

[79]  Arun Ross,et al.  Synthesizing Iris Images Using RaSGAN With Application in Presentation Attack Detection , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[80]  Julien Bringer,et al.  Security analysis of Bloom filter-based iris biometric template protection , 2015, 2015 International Conference on Biometrics (ICB).

[81]  Andrew Beng Jin Teoh,et al.  Cancellable biometrics and annotations on BioHash , 2008, Pattern Recognit..

[82]  Julian Fiérrez,et al.  Face verification put to test: A hill-climbing attack based on the uphill-simplex algorithm , 2012, 2012 5th IAPR International Conference on Biometrics (ICB).

[83]  Davide Maltoni,et al.  The magic passport , 2014, IEEE International Joint Conference on Biometrics.

[84]  Sargur N. Srihari,et al.  Image Pattern Recognition - Synthesis and Analysis in Biometrics , 2007, Image Pattern Recognition.

[85]  Arun Ross,et al.  Iris image reconstruction from binary templates: An efficient probabilistic approach based on genetic algorithms , 2013, Comput. Vis. Image Underst..

[86]  Julien Bringer,et al.  Privacy-Preserving Biometric Identification Using Secure Multiparty Computation: An Overview and Recent Trends , 2013, IEEE Signal Processing Magazine.

[87]  Vitaly Shmatikov,et al.  Membership Inference Attacks Against Machine Learning Models , 2016, 2017 IEEE Symposium on Security and Privacy (SP).

[88]  Patrizio Campisi,et al.  Hill-Climbing Attacks on Multibiometrics Recognition Systems , 2015, IEEE Transactions on Information Forensics and Security.

[89]  Eric Moulines,et al.  Voice transformation using PSOLA technique , 1991, Speech Commun..

[90]  Andreas Uhl,et al.  Attacking Iris Recognition: An Efficient Hill-Climbing Technique , 2010, 2010 20th International Conference on Pattern Recognition.

[91]  Christoph Busch,et al.  Unlinkable and irreversible biometric template protection based on bloom filters , 2016, Inf. Sci..

[92]  Julian Fiérrez,et al.  Multi-biometric template protection based on Homomorphic Encryption , 2017, Pattern Recognit..

[93]  Alessandra Lumini,et al.  An evaluation of direct attacks using fake fingers generated from ISO templates , 2010, Pattern Recognit. Lett..

[94]  Luuk J. Spreeuwers,et al.  Face reconstruction from image sequences for forensic face comparison , 2016, IET Biom..

[95]  Zhouchen Lin,et al.  Style-preserving English handwriting synthesis , 2007, Pattern Recognit..

[96]  Christoph Busch,et al.  Improved Fuzzy Vault Scheme for Alignment-Free Fingerprint Features , 2015, 2015 International Conference of the Biometrics Special Interest Group (BIOSIG).

[97]  Arun Ross,et al.  On Mixing Fingerprints , 2013, IEEE Trans. Inf. Forensics Secur..

[98]  Andy Adler Sample images can be independently restored from face recognition templates , 2003, CCECE 2003 - Canadian Conference on Electrical and Computer Engineering. Toward a Caring and Humane Technology (Cat. No.03CH37436).

[99]  Sébastien Marcel,et al.  Biometric Systems under Morphing Attacks: Assessment of Morphing Techniques and Vulnerability Reporting , 2017, 2017 International Conference of the Biometrics Special Interest Group (BIOSIG).

[100]  Stefanos Zafeiriou,et al.  GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[101]  Vincenzo Piuri,et al.  Biometric Recognition in Automated Border Control , 2016, ACM Comput. Surv..

[102]  Junichi Yamagishi,et al.  Revisiting the security of speaker verification systems against imposture using synthetic speech , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

[103]  Abdenour Hadid,et al.  Biometrics Systems Under Spoofing Attack: An evaluation methodology and lessons learned , 2015, IEEE Signal Processing Magazine.

[104]  Anil K. Jain,et al.  Biometric Template Protection: Bridging the performance gap between theory and practice , 2015, IEEE Signal Processing Magazine.

[105]  Jaakko Lehtinen,et al.  Progressive Growing of GANs for Improved Quality, Stability, and Variation , 2017, ICLR.

[106]  Davide Maltoni,et al.  On the Generation of Synthetic Fingerprint Alterations , 2016, 2016 International Conference of the Biometrics Special Interest Group (BIOSIG).

[107]  Caroline Fontaine,et al.  A Survey of Homomorphic Encryption for Nonspecialists , 2007, EURASIP J. Inf. Secur..

[108]  Ajmal Mian,et al.  Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey , 2018, IEEE Access.

[109]  Mauro Barni,et al.  Encrypted signal processing for privacy protection: Conveying the utility of homomorphic encryption and multiparty computation , 2013, IEEE Signal Processing Magazine.

[110]  Nalini K. Ratha,et al.  Enhancing security and privacy in biometrics-based authentication systems , 2001, IBM Syst. J..

[111]  Julien Bringer,et al.  GSHADE: faster privacy-preserving distance computation and biometric identification , 2014, IH&MMSec '14.

[112]  Yoshua Bengio,et al.  Generative Adversarial Networks , 2014, ArXiv.