Abstract
Multi-biometric systems have several advantages over uni-biometrics based systems, such as, better verification accuracy, larger feature space to accommodate more subjects, and higher security against spoofing. Unfortunately, as in case of uni-biometric systems, multi-biometric systems also face the problems of nonrevocability, lack of template diversity, and possibility of privacy compromise. A combination of biometrics and cryptography is a good solution to eliminate these limitations. In this chapter we present a multi-biometric cryptosystem based on the fuzzy commitment scheme, in which, a crypto-biometric key is derived from multi-biometric data. An idea (recently proposed by the authors) denoted as FeaLingECc (Feature Level Fusion through Weighted Error Correction) is used for the multi-biometric fusion. The FeaLingECc allows fusion of different biometric modalities having different performances (e.g., face + iris). This scheme is adapted for a multi-unit system based on two-irises and a multi-modal system using a combination of iris and face. The difficulty in obtaining the crypto-biometric key locked in the system (and in turn the reference biometric data) is 189 bits for the two-iris system while 183 bits for the iris-face system using brute force attack. In addition to strong keys, these systems possess revocability and template diversity and protect user privacy.
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References
Beveridge JR, Bolme D, Raper BA, Teixeira M (2005) The CSU face identification evaluation system. Machine Vision and Applications 16(2):128–138
Biosecure Tool (2007) Performance evaluation of a biometric verification system. Online. http://svnext.it-sudparis.eu/svnview2-eph/ref_syst/Tools/PerformanceEvaluation/doc/
Boyen X (2004) Reusable cryptographic fuzzy extractors. In: 11th ACM Conference on Computer and Communications Security (CCS)
Burr WE, Dodson DF, Polk WT (2006) Electronic authentication guideline. Recommendations of the National Institute of Standards and Technology
Cimato S, Gamassi M, Piuri V, Sassi R, Scotti F (2008) Privacy-aware biometrics: design and implementation of a multimodal verification system. In: Annual Computer Security Applications Conference (ACSAC). doi:10.1109/ACSAC.2008.13
Daugman J (2003) The importance of being random: statistical principles of iris recognition. Pattern Recognition 36(2):279–291
Dodis Y, Reyzin L, Smith A (2004) Fuzzy extractors: how to generate strong keys from biometrics and other noisy data. In: Proceedings of the Eurocrypt 2004, pp 523–540
Fu B, Yang SX, Li J, Hu D (2009) Multibiometric cryptosystem: model structure and performance analysis. IEEE Transactions on Information Forensics and Security 4(4):867–882
Hao F, Anderson R, Daugman J (2006) Combining crypto with biometrics effectively. IEEE Transactions on Computers 55(9):1081–1088
Jain AK, Nandakumar K, Nagar A (2008) Biometric template security. EURASIP Journal on Advances in Signal Processing 2008:579416. 17 pp. doi:10.1155/2008/579416
Juels A, Sudan M (2002) A fuzzy vault scheme. In: Lapidoth A, Teletar E (eds) Proc IEEE Int Symp Information Theory. IEEE Press, New York, p 408
Juels A, Wattenberg M (1999) A fuzzy commitment scheme. In: Proceedings of the Sixth ACM Conference on Computer and Communication Security (CCCS), pp 28–36
Kanade S, Camara D, Krichen E, Petrovska-Delacrétaz D, Dorizzi B (2008) Three factor scheme for biometric-based cryptographic key regeneration using iris. In: The 6th Biometrics Symposium (BSYM)
Kanade S, Petrovska-Delacrétaz D, Dorizzi B (2009) Cancelable iris biometrics and using error correcting codes to reduce variability in biometric data. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Kanade S, Petrovska-Delacrétaz D, Dorizzi B (2009) Multi-biometrics based cryptographic key regeneration scheme. In: IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS)
Kanade S, Petrovska-Delacrétaz D, Dorizzi B (2010) Obtaining cryptographic keys using feature level fusion of iris and face biometrics for secure user authentication. In: IEEE CVPR Workshop on Biometrics
Kelkboom E, Zhou X, Breebaart J, Veldhuis R, Busch C (2009) Multi-algorithm fusion with template protection. In: IEEE Second International Conference on Biometrics Theory, Applications and Systems
Kovesi P (2005) Matlab and octave functions for computer vision and image processing. Online. http://www.csse.uwa.edu.au/~pk/Research/MatlabFns/
Lades M, Vorbrüuggen JC, Buhmann J, Lange J, von der Malsburg C, Wüurtz RP, Konen W (1993) Distortion invariant object recognition in the dynamic link architecture. IEEE Transactions on Computers 42(3):300–311
Lumini A, Nanni L (2007) An improved biohashing for human authentication. Pattern Recognition 40(3):1057–1065. doi:10.1016/j.patcog.2006.05.030
MacWilliams FJ, Sloane NJA (1991) Theory of Error-Correcting Codes. North Holland, Amsterdam
Maiorana E, Campisi P, Ortega-Garcia J, Neri A (2008) Cancelable biometrics for HMM-based signature recognition. In: IEEE Conference on Biometrics: Theory, Applications and Systems (BTAS)
Nandakumar K (2008) Multibiometric systems: fusion strategies and template security. Phd thesis, Department of Computer Science and Engineering, Michigan State University
Nandakumar K, Jain AK (2008) Multibiometric template security using fuzzy vault. In: IEEE Second International Conference on Biometrics: Theory, Applications and Systems
National Institute of Science and Technology (NIST) (2005) Face recognition grand challenge. http://www.frvt.org/FRGC/
National Institute of Science and Technology (NIST) (2005) Iris challenge evaluation. http://iris.nist.gov/ice
Petrovska-Delacrétaz D, Chollet G, Dorizzi B (eds) (2009) Guide to Biometric Reference Systems and Performance Evaluation. Springer, Berlin
Ratha NK, Chikkerur S, Connell JH, Bolle RM (2007) Generating cancelable fingerprint templates. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(4):561–572. doi:10.1109/TPAMI.2007.1004
Ross AA, Nandakumar K, Jain AK (2006) Handbook of Multibiometrics. International Series on Biometrics. Springer, Berlin
Stoianov A (2010) Security of error correcting code for biometric encryption (critical note). In: Eighth Annual International Conference on Privacy, Security and Trust
Sutcu Y, Li Q, Memon N (2007) Secure biometric templates from fingerprint-face features. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 1–6. doi:10.1109/CVPR.2007.383385
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Kanade, S., Petrovska-Delacrétaz, D., Dorizzi, B. (2013). Obtaining Cryptographic Keys Using Multi-biometrics. In: Campisi, P. (eds) Security and Privacy in Biometrics. Springer, London. https://doi.org/10.1007/978-1-4471-5230-9_6
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DOI: https://doi.org/10.1007/978-1-4471-5230-9_6
Publisher Name: Springer, London
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