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| A Novel Biometric Technique Benchmark Analysis For Selection Of Best Biometric Modality And Template Generation Method
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Source |
International Journal of Biometrics and Bioinformatics (IJBB) |
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Table of Contents |
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Complete Issue PDF(5.66MB) |
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Volume: 5 Issue: 2 |
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Pages: 28-148 |
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Publication
Date: May / June 2011 |
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ISSN
(Online): 1985-2347 |
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76 - 96 |
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Author(s) |
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Published
Date |
31-05-2011 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
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KEYWORDS: Biometric Template Security, Template Invariability, Template Quality Analysis |
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| A biometric security is a technique by means of which digital contents are protected by a cryptographic key generated from the biometric features of a person like Retina, Iris, Fingerprint, Face, Voice and so on. Normally the digital contents like documents are protected by a cryptographic key generated from a unique password. The process in irreversible, i.e the key can be generated from the password but not the vice versa. Passwords are relatively easy to hack as most of the users keep their personal information like date of birth as password and also password length has a limit as human beings cannot remember a password of significantly large length. Hence guessing the password of a user, whose significant information is available, is easier. Therefore off late lot of emphasis has been given to biometric features. Biometric features of no two people are same. For example the finger prints or the face of any two people differ. Hence if a template (alphanumeric or binary representation of features from a biometric data) is selected for the key generation than cracking them for accessing information becomes significantly difficult. But as with every advantage comes certain limitations also. The keys are not time invariant. Templates tends to change based on the data acquisition, or with time. For example the finger prints or palm prints changes with ages. Iris, retina and face features changes with change in light intensity during the acquisition phase. Fingerprint features changes with change in the orientation of the finger while scanning. In a classic authentication problem, such variability’s can be easily dealt with by keeping a threshold for the acceptance of the features. Such acceptance threshold is not applicable for the case of biometric templates. Even slightest of the variability in the templates changes the generated key, therefore causing a high false rejection rate. Hence in this work we analyze the most accepted biometric features and techniques for key generation and propose the most invariable technique in terms of data acquisition invariability. The work analyzes Iris, Face, Fingerprint and Palm prints for analysis of the biometric template generation and key generation form the templates. Further a unique benchmark analysis technique is proposed for quantifying the quality of a biometric model or features. |
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| 1 |
Magnus Pettersson, “The Match On Card Technology”, Precise Biometrics White Paper
|
|
|
| 2 |
Ricardo García Noval, Francisco Perales López, “Poster: Adaptative Templates In Biometric Authentication”
|
|
|
| 3 |
Lucas Ballard, Seny Kamara, Michael K. Reiter, “The Practical Subtleties of Biometric Key Generation”, 17th USENIX Security Symposium
|
|
|
| 4 |
C. Chen, R.N.J. Veldhuis, T.A.M. Kevenaar, A.H.M. Akkermans, “Multi-Bits Biometric String Generation based on the Likelihood Ratio”, DOI: Multi-Bits Biometric String Generation based on the Likelihood Ratio,IEEE, 2007
|
|
|
| 5 |
U. Korte, R. Plaga, “Cryptographic Protection of Biometric Templates: Chance, Challenges and Applications”
|
|
|
| 6 |
Aditya Abhyankar , Stephanie Schuckers, “Novel Biorthogonal Wavelet based Iris Recognition for Robust Biometric System”, International Journal of Computer Theory and Engineering, Vol. 2, No. 2 April, 2010 1793-8201
|
|
|
| 7 |
James L. Maseey, “Guessing and Entropy”,DOI: 0 - 7803-2015-8/94, IEEE,1994
|
|
|
| 8 |
Asker M. Bazen and Raymond N. J. Veldhuis, “Likelihood-Ratio-Based Biometric Verification”, Ieee Transactions On Circuits And Systems For Video Technology, Vol. 14, No. 1, January 2004, 1051-8215/04,Ieee, 2004
|
|
|
| 9 |
C. K. CHOW, “On Optimum Recognition Error and Reject Tradeoff”, IEEE Tr.4nsactions On Information Theory, Vol. It-16, No. 1, January 1970
|
|
|
| 10 |
C. K. CHOW, “An Optimum Character Recognition System Using Decision Functions”, PGEC, June 3, 1957
|
|
|
| 11 |
Juels A. and Wattenberg M., "A Fuzzy Commitment Scheme", ACM Conference on Computer and Communications Security", 1999, p.28-36
|
|
|
| 12 |
Daniel Gonz´alez-Jim´enez and Jos´e Luis Alba-Castro, “Modeling Marginal Distributions of Gabor Coefficients: Application to Biometric TemplateReduction”, project PRESA TEC2005-07212
|
|
|
| 13 |
V. S. Meenakshi and Dr G. Padmavathi, “Securing Revocable Iris and Retinal Templates using Combined User and Soft Biometric based Password Hardened Multimodal Fuzzy Vault”, IJCSI International Journal of Computer Science Issues, Vol. 7, Issue 5, September 2010 ISSN (Online): 1694-0814
|
|
|
| 14 |
Anil Jain, Umut Uludag and Arun Ross, “Biometric Template Selection: A Case Study in Fingerprints”, Proc. of 4th Int'l Conference on Audio- and Video-Based Person Authentication (AVBPA), LNCS 2688, pp. 335-342, Guildford, UK, June 9-11, 2003.
|
|
|
| 15 |
Aditya Abhyankar and Stephanie Schuckers, “Novel Biorthogonal Wavelet based Iris Recognition for Robust Biometric System”, International Journal of Computer Theory and Engineering, Vol. 2, No. 2 April, 2010 1793-8201
|
|
|
| 16 |
Abhishek Nagar, Karthik Nandakumar, and A. K. Jain, “Biometric template security”, SPIE, 10.1117/2.1200911.001590
|
|
|
| 17 |
Julien Bringer, Herve Chabanne, David Pointcheval, and Sebastien Zimmer, “An Application of the Boneh and Shacham Group Signature Scheme to Biometric Authentication”, Springer-Verlag 2008
|
|
|
| 18 |
Qinghan Xiao, “Security Issues in Biometric Authentication”, Proceedings of the 2005 IEEE,Workshop on Information Assurance and Security, United States Military Academy, West Point, NY
|
|
|
| 19 |
Yunsu Chung, Kiyoung Moon, Hyung-Woo Lee, “Biometric Certificate based Biometric Digital Key Generation with Protection Mechanism”, Frontiers in the Convergence of Bioscience and Information Technologies 2007
|
|
|
| 20 |
Andrew Beng Jin Teoh, Thian Song Ong, “Secure Biometric Template Protection via Randomized Dynamic Quantization Transformation”, 1-4244-2427-6/08,IEEE
|
|
|
| 21 |
Brenden Chen and Vinod Chandran, “Biometric Template Security Using Higher Order Spectra”, 978-1-4244-4296-6/10, IEEE,2010
|
|
|
| 22 |
Qinghai Gao, Xiaowen Zhang, and Michael Anshel, “Experiments on Matching Intronized Fingerprint Minutiae Templates”, IJCSNS International Journal of Computer Science and Network Security, VOL.8 No.9, September 2008
|
|
|
| 23 |
Andy Adler, “Vulnerabilities in biometric encryption systems”, IST-044-RWS-007
|
|
|
| 24 |
Michael Braithwaite, Ulf Cahn von Seelen, James Cambier,, “Application-Specific Biometric Templates”
|
|
|
| 25 |
E. Verbitskey,D. Denteneer, P. tuylys, “Reliable biometric authentication with privacy protection.”
|
|
|
| 26 |
Anil K. Jain, Karthik Nandakumar, and Abhishek Nagar, “Biometric Template Security”, EURASIP Journal on Advances in Signal Processing Volume 2008, Article ID 579416, 17 pages, doi:10.1155/2008/579416
|
|
|
| 27 |
Shih-Wei Sun¤y, Chun-Shien Lu¤, and Pao-Chi Changy, “Biometric Template Protection: A Key-Mixed Template Approach”, 1-4244-0763-X/07, IEEE, 2007
|
|
|
| 28 |
Morpho, “Automatic Facial Recognition: A review”, SAFRON
|
|
|
| 29 |
Tony Mansfield, Marek R. G., “Feasibility study on the use of biometric in an Entitlement scheme, Biometric Feasibility Study”, Version 3, 2003
|
|
|
| 30 |
Srinivasa Palla, Sharat S. Chikkerur, Venu Govindaraju, Pavan Rudravaram, “Classification and Indexing in Large Biometric Databases”
|
|
|
| 31 |
Tarachand Verma, Prof. Richa Jindal, Prof. Sonika Jindal, “A Security Algorithm For Iris Based Biometric System”, International Journal Of Engineering Science And Technology, Vol. 2(06), 2010, 2316-2320
|
|
|
| 32 |
Yong Li, Jianping Yin, En Zhu, Chunfeng Hu, Hui Chen, “Score Based Biometric Template Selection”, 978-1-4244-2175-6/08/, IEEE, 2008
|
|
|
| 33 |
Luisa Riccardi, Bruno Peticone and Mario Savastano, “Biometrics for massive access control Traditional Problems and Innovative Approaches”, Proceedings of the 2005 IEEE Workshop on Information Assurance and Security United States Military Academy, West Point, NY
|
|
|
| 34 |
C.Lakshmi Deepika, A.Kandaswamy, “An Algorithm for Improved Accuracy in Unimodal Biometric Systems through Fusion of Multiple Feature Sets”, ICGST-GVIP Journal, ISSN 1687-398X, Volume (9), Issue (III), June 2009
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| Sharanabasappa Raikoti : Colleagues
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| Sanjaypande M. B.2 : Colleagues
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