article

An overview of protection of privacy in multibiometrics

Authors:

Iynkaran Natgunanathan,

Shaun BangayAuthors Info & Claims

Multimedia Tools and Applications, Volume 77, Issue 6

Pages 6753 - 6773

https://doi.org/10.1007/s11042-017-4596-y

Published: 01 March 2018 Publication History

Abstract

Biometric authentication systems (BASs) have various advantages over traditional authentication systems such as password based systems. In BASs, information related to individuals' physical and psychological characteristics is employed for authentication. The leakage of such information will breach individuals' privacy severely. To simultaneously protect privacy and achieve higher authentication accuracy, privacy preserving multibiometric authentication systems (PPMASs) have been developed. This paper provides a comprehensive review of PPMASs. Specifically, we outline the requirements of PPMASs and discuss the state-of-the-art PPMASs. We also discuss PPMASs in the context of mobile and cloud based applications. Furthermore, we show the drawbacks of the existing PPMASs and point out the future research directions of PPMASs.

References

[1]

Arandjelovic O, Hammoud R (2006) Multi-sensory face biometric fusion (for personal identification). In: Conf. comput. vision and pattern recognit., pp 1---8

Digital Library

[2]

Aronowitz H, Li M, Toledo-Ronen O, Harary S, Geva A, Ben-David S, Rendel A, Hoory R, Ratha N, Pankanti S, Nahamoo D (2014) Multi-modal biometrics for mobile authentication. In: IEEE Int. conf. biometrics, pp 1---8

[3]

Blanton M, Aliasgari M (2013) Analysis of reusability of secure sketches and fuzzy extractors. IEEE Trans Inf Forens Secur 8(9):1433---1445

Digital Library

[4]

Boyen X (2004) Reusable cryptographic fuzzy extractors. In: ACM conf. comput. and commun. security, pp 82---91

Digital Library

[5]

Bringer J, Chabanne H, Cohen G, Kindarji B, Zemor G (2007) Optimal iris fuzzy sketches. In: IEEE Int. conf. on biometrics: Theory, Applicat., and Syst., pp 1---6

[6]

Chetty G, Wagner M (2006) Multilevel liveness verification for face-voice biometric authentication. In: Biometrics symp.: special session on research at the biometric consortium conf., pp 1---6

[7]

Dandawate YH, Inamdar SR (2015) Fusion based multimodal biometric cryptosystem. In: Int. conf. ind. instrumentation and control, pp 1484---1489

[8]

Dass SC, Nandakumar K, Jain AK (2005) A principled approach to score level fusion in multimodal biometric systems. In: 5th Int. conf. audio and video-based biometric person authent., pp 1049---1058

Digital Library

[9]

Daugman J (2000) Combining multiple biometrics. {Online}. http://www.cl.cam.ac.uk/~jgd1000/combine/combine.html

[10]

Daugman J (2004) Iris recognition and anti-spoofing countermeasures. In: Int. biometrics conf

[11]

Derawi MO, Gafurov D, Larsen R, Busch C, Bours P (2010) Fusion of gait and fingerprint for user authentication on mobile devices. In: 2nd Int. Workshop security and commun. networks, pp 1---6

[12]

Gawande U, Hajari KO, Golhar YG (2014) Novel cryptographic algorithm based fusion of multimodal biometrics authentication system. In: Int. conf. comput. and commun. technol., pp 1---6

[13]

Hong L, Jain AK (1998) Integrating faces and fingerprints for personal identification. IEEE Trans Pattern Anal Mach Intell 20(12):1295---1307

Digital Library

[14]

Iida K, Kiya H (2016) Secure and robust identification based on fuzzy commitment scheme for JPEG images. In: IEEE Int. symp. on broadband multimedia syst. and broadcast., pp 1---5

[15]

Jain AK, Uludag U (2002) Hiding fingerprint minutiae in images. In: 3rd Workshop automatic identification advanced tech., pp 97---102

[16]

Jain AK, Uludag U, Hsu RL (2002) Hiding a face in a fingerprint image. In: Int. conf. pattern recognit., pp 756---759

Digital Library

[17]

Jain AK, Nandakumar K, Nagar A (2008) Biometric template security. EURASIP. J Adv Signal Process 2008:1---17

Digital Library

[18]

Jin ATB, Ling DN, Goh A (2008) Biohashing: two factor authentication featuring fingerprint data and tokenised random number. Pattern Recogn 37(11):2245---2255

Digital Library

[19]

JTC1 SC27 IT Security Techniques (2011) ISO/IEC 24745: biometric information protection, Intl Organization for Standardization (ISO)

[20]

Juels A, Wattenberg M (1999) A fuzzy commitment scheme. In: ACM conf. comput. and commun. security, pp 28---36

Digital Library

[21]

Kaur H, Khanna P (2015) Biometric template protection using cancelable biometrics and visual cryptography techniques. Multimedia Tools Appl:1---29.

Digital Library

[22]

Kumar A, Wong DC, Shen HC, Anil KJ (2003) Personal verification using palmprint and hand geometry biometric, vol 2688. Springer, Heidelberg, pp 668---678

Digital Library

[23]

Lam L, Suen CY (1995) Optimal combination of pattern classifiers. Pattern Recogn Lett 16(9): 945---954

Digital Library

[24]

Lam L, Suen CY (1997) Application of majority voting to pattern recognition: An analysis of its behavior and performance. IEEE Trans Syst Man Cybern Part A: Syst Humans 27(5):553---568

Digital Library

[25]

Li Q, Guo M, Chang E-C (2008) Fuzzy extractors for asymmetric biometric representations. In: IEEE workshop on biometrics (in association with CVPR), pp 1---6

[26]

Li C, Hu J, Pieprzyk J, Susilo W (2015) A new biocryptosystem-oriented security analysis framework and implementation of multibiometric cryptosystems based on decision level fusion. IEEE Trans Inf Forens Secur 10(6):1193---1206

Digital Library

[27]

Liu Y, Hatzinakos D (2015) Biohashing for human acoustic signature based on random projection. Cand J Elect Comput Eng 38(3):66---273

[28]

Nagar A, Nandakumar K, Jain AK (2012) Multibiometric cryptosystems based on feature-level fusion. IEEE Trans Inf Forens Secur 7(1):255---268

Digital Library

[29]

Nandakumar K, Jain AK (2008) Multibiometric template security using fuzzy vault. In: IEEE Int. conf. biometrics: theory, applicat. and syst., pp 1---6

[30]

Nandakumar K, Jain AK (2015) Biometric template protection: bridging the performance gap between theory and practice. IEEE Signal Process Mag 32(5):88---100

[31]

Nandakumar K, Jain AK, Pankanti S (2007) Fingerprint-based fuzzy vault: implementation and performance. IEEE Trans Inf Forens Secur 2(4):744---757

Digital Library

[32]

Natgunanathan I, Xiang Y, Rong Y, Zhou W, Guo S (2012) Robust patchwork-based embedding and decoding scheme for digital audio watermarking. IEEE Trans Audio Speech Lang Process 20(8):2232---2239

Digital Library

[33]

Natgunanathan I, Xiang Y, Rong Y, Peng D (2013) Robust patchwork-based watermarking method for stereo audio signals. Multimedia Tools Appl 72(2):1---24

Digital Library

[34]

Nguyen TH, Wang Y, Ha Y, Li R (2013) Improved chaff point generation for vault scheme in bio-cryptosystems. IET Biometrics 2(2):48---55

[35]

Nguyen TAT, Dang TK (2015) Combining fuzzy extractor in biometric-kerberos based authentication protocol. In: Int. conf. on advanced comput. and appl., pp 1---6

Digital Library

[36]

Ong TS, Teng JH, Muthu KS, Teoh ABJ (2013) Multi-instance finger vein recognition using minutiae matching. In: Int. congress on image and signal process., pp 1730---1735

[37]

Ramalho MB, Correia PL, Soares LD (2012) Hand-based multimodal identification system with secure biometric template storage. IET Comput Vis 6 (3):165---173

[38]

Ratha NK, Connell JH, Bok RM (2000) Secure data hiding in wavelet compressed fmgerprint images. In: ACM Multimedia workshops, pp 127---130

Digital Library

[39]

Ratha NK, Connell JH, Bolle RM (2001) Enhancing security and privacy in biometrics-based authentication systems. IBM Syst J 40(3):614---634

Digital Library

[40]

Ratha NK, Chikkerur S, Connell JH, Bolle RM (2007) Generating cancelable fingerprint templates. IEEE Trans Pattern Anal Mach Intell 29(4):561---572

Digital Library

[41]

Ross A, Jain AK (2003) Information fusion in biometrics. Pattern Recogn Letts 24:2125---2215

Digital Library

[42]

Rudrakshi PG, Hatture SKM (2014) A model for secure information storage and retrieval on cloud using multimodal biometric cryptosystem. In: Int. conf. computer and commun. technol., pp 169---174

[43]

Safie SI, Nurfazira H, Azavitra Z, Soraghan JJ, Petropoulakis L (2014) Pulse active transform: a non-invertible transformation with application to ECG biometric authentication. In: Region 10 symp., pp 667---671

[44]

Sim T, Jankiraman R, Kumar S (2007) Continuous verification using multimodal biometrics. IEEE Trans Pattern Anal Mach Intell 29(4):687---700

Digital Library

[45]

Sun D, Li Q, Liu T, He B, Qiu Z (2005) A secure multimodal biometric verification scheme. In: Advances in biometric person authentication (lecture notes computer science), vol 3781, pp 233---240

Digital Library

[46]

Sutcu Y, Li Q, Memon N (2007) Secure biometric templates from fingerprint-face features. In: IEEE conf. comput. vision and pattern recognit., pp 1---6

[47]

Tams B (2016) Unlinkable minutiae-based fuzzy vault for multiple fingerprints. IET Biometrics 5(3):170---180

[48]

Teoh ABJ, Yuang CT (2007) Cancelable biometrics realization with multispace random projections. IEEE Trans Syst Man Cybern Part B 37(5):840---854

Digital Library

[49]

Teoh A, Kim J (2007) Secure biometric template protection in fuzzy commitment scheme. IEICE Electron Express 4(23):724---730

[50]

Teoh AB, Kuan YW, Lee S (2008) Cancellable biometrics and annotations on biohash. Pattern Recogn 41(6):2034---2044

Digital Library

[51]

Thepade SD, Bhondave RK (2015) Novel multimodal identification technique using iris & palmprint traits with various matching score level proportions using BTC of bit plane slices. In: Int. conf. pervasive comput., pp 1---4

[52]

Vatsa M, Singh R, Mitra P, Noore A (2004) Digital watermarking based secure multimodal biometric system. In: IEEE Int. conf. syst., man, and cybernetics, pp 2983---2987

[53]

Vildjiounaite E, Makela S-M, Lindholm M, Kyllonen V, Ailisto H (2007) Increasing security of mobile devices by decreasing user effort in verification. In: 2nd Int. conf. syst. and networks commun., pp 80---86

Digital Library

[54]

Wang D, Li J, Memik G (2009) Authentication scheme of DRM system for remote users based on multimodal biometrics, watermarking and smart cards. In: Global congress intell. syst., pp 530---534

Digital Library

[55]

Whitelam C, Osia N, Bourlai T (2013) Securing multimodal biometric data through watermarking and steganography. In: IEEE Int. conf. tech. for homeland security, pp 61---66

[56]

Xu L, Krzyzak A, Suen CY (1992) Methods for combining multiple classifiers and their applications to handwriting recognition. IEEE Trans Syst Man Cybern 22 (3):418---435

[57]

Zong T, Xiang Y, Natgunanathan I, Guo S, Zhou W, Beliakov G (2015) Robust histogram shape-based method for image watermarking. IEEE Trans Circ Syst Video Technol 25(5):717---729

Cited By

Xu ZShao ZShang YLi BDing HLiu T(2021)Fusing structure and color features for cancelable face recognitionMultimedia Tools and Applications10.1007/s11042-020-10234-880:9(14477-14494)Online publication date: 1-Apr-2021
https://dl.acm.org/doi/10.1007/s11042-020-10234-8
Khan RLone S(2021)A comprehensive study of document security system, open issues and challengesMultimedia Tools and Applications10.1007/s11042-020-10061-x80:5(7039-7061)Online publication date: 1-Feb-2021
https://dl.acm.org/doi/10.1007/s11042-020-10061-x
Abdellatef EIsmail NAbd Elrahman SIsmail KRihan MAbd El-Samie F(2020)Cancelable multi-biometric recognition system based on deep learningThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-019-01715-536:6(1097-1109)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1007/s00371-019-01715-5

An overview of protection of privacy in multibiometrics
1. Computing methodologies
2. Security and privacy
  1. Security services

Recommendations

An effective iris biometric privacy protection scheme with renewability
Abstract
Iris is considered a unique, robust biometric that can be used as an authentication factor. Privacy protection of individuals’ iris templates is an essential requirement. The essential attributes needed to ensure privacy of biometrics are ...
Genetic programming for multibiometrics

Biometric systems suffer from some drawbacks: a biometric system can provide in general good performances except with some individuals as its performance depends highly on the quality of the capture... One solution to solve some of these problems is to ...
Fusion of electrocardiogram with unobtrusive biometrics: An efficient individual authentication system

This paper explores the effectiveness of a novel multibiometric system that is resulted from the fusion of the electrocardiogram (ECG) with an unobtrusive biometric face and another biometric fingerprint which is known to be a least obtrusive for ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Multimedia Tools and Applications

Multimedia Tools and Applications Volume 77, Issue 6

March 2018

1338 pages

ISSN:1380-7501

Issue’s Table of Contents

Copyright © Copyright © 2018 Springer Science+Business Media, LLC, part of Springer Nature.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 March 2018

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 19 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Xu ZShao ZShang YLi BDing HLiu T(2021)Fusing structure and color features for cancelable face recognitionMultimedia Tools and Applications10.1007/s11042-020-10234-880:9(14477-14494)Online publication date: 1-Apr-2021
https://dl.acm.org/doi/10.1007/s11042-020-10234-8
Khan RLone S(2021)A comprehensive study of document security system, open issues and challengesMultimedia Tools and Applications10.1007/s11042-020-10061-x80:5(7039-7061)Online publication date: 1-Feb-2021
https://dl.acm.org/doi/10.1007/s11042-020-10061-x
Abdellatef EIsmail NAbd Elrahman SIsmail KRihan MAbd El-Samie F(2020)Cancelable multi-biometric recognition system based on deep learningThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-019-01715-536:6(1097-1109)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1007/s00371-019-01715-5

View Options

View options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Issue’s Table of Contents