Security Analysis of Password Hardened Multimodal Biometric Fuzzy Vault

Biometric techniques are gaining importance for personal authentication and identification as compared to the traditional authentication methods. Biometric templates are vulnerable to variety of attacks due to their inherent nature. When a person-s biometric is compromised his identity is lost. In contrast to password, biometric is not revocable. Therefore, providing security to the stored biometric template is very crucial. Crypto biometric systems are authentication systems, which blends the idea of cryptography and biometrics. Fuzzy vault is a proven crypto biometric construct which is used to secure the biometric templates. However fuzzy vault suffer from certain limitations like nonrevocability, cross matching. Security of the fuzzy vault is affected by the non-uniform nature of the biometric data. Fuzzy vault when hardened with password overcomes these limitations. Password provides an additional layer of security and enhances user privacy. Retina has certain advantages over other biometric traits. Retinal scans are used in high-end security applications like access control to areas or rooms in military installations, power plants, and other high risk security areas. This work applies the idea of fuzzy vault for retinal biometric template. Multimodal biometric system performance is well compared to single modal biometric systems. The proposed multi modal biometric fuzzy vault includes combined feature points from retina and fingerprint. The combined vault is hardened with user password for achieving high level of security. The security of the combined vault is measured using min-entropy. The proposed password hardened multi biometric fuzzy vault is robust towards stored biometric template attacks.




References:
[1] Umat uludag, sharath pankanti, Anil. K.Jain "Fuzzy vault for
fingerprints", Proceedings of International conference on Audio video
based person authentication, july 20 - 22, pp. 310 - 319, 2005.
[2] A. Juels and M.Sudan, "A fuzzy vault scheme", Proceedings of IEEE
International symposium Information Theory, pp. 408, 2002.
[3] E.Srinivasa Reddy, I. Ramesh Babu, "Performance of Iris Based Hard
Fuzzy Vault", Proceedings of IEEE 8th International conference on
computers and Information technology workshops, pp. 248 - 253, 2008
[4] U.Uludag, S. Pankanti, S.Prabhakar, and A.K.Jain, "Biometric
Cryptosystems: issues and challenges, Proceedings of the IEEE
92(6): 948 - 960,June , 2004.
[5] Karthik Nandakumar, Abhishek Nagar and Anil K.Jain, "Hardening
Fingerprint Fuzzy Vault using Password", International conference on
Biometrics, pp. 927 - 938, 2007.
[6] Karthick Nandakumar, Sharath Pankanti, Anil K. Jain, "Fingerprintbased
Fuzzy Vault Implementation and Performance", IEEE
Transacations on Information Forensics and Security, 2(4):744 - 757,
December 2007.
[7] K.NandaKumar, "Multibiometric Systems: Fusion Strategies and
Template Security", PhD Thesis, Department of Computer Science and
Engineering, Michigan State University, January 2008.
[8] Sharat Chikkarur, Chaohang Wu, Venu Govindaraju, "A systematic
Approach for feature Extraction in Fingerprint images", Center for
Unified Biometrics and Sensors(CUBS), university at Buffalo, NY,USA.
[9] A. K. Jain, A. Ross, and S. Pankanti, "Biometrics: A Tool for
Information Security," IEEE Transactions on Information Forensics and
Security, vol. 1, no. 2, pp. 125-143, June 2006.
[10] A. K. Jain, A. Ross, and U. Uludag, "Biometric Template Security:
Challenges and Solutions," in Proceedings of European Signal
Processing Conference (EUSIPCO), Antalya, Turkey, September 2005.
[11] Anil K.Jain, Karthik Nanda Kumar and Abhishek Nagar, "Biometric
Template Security" EURASIP Journal on Advance in Signal Processing,
special issue on Biometrics, January 2008.
[12] Ratha, N.K., J.H. Connell, and R.M. Bolle, "Enhancing security and
privacy in biometrics-based authentication systems", IBM Systems
Journal, vol. 40, no. 3, pp. 614 - 634, 2001.
[13] Jain, Anil K. Jain and Arun Ross, "Multibiometric systems,"
Communications of the ACM," January 2004, Volume 47, Number 1
(2004).
[14] A.K. Jain and A. Ross, "Learning User-specific parameters in a
Multibiometric System", Proc. IEEE International Conference on Image
Processing(ICIP), Rochester, New York, pp. 57 - 60, September 22 -
25, 2002.
[15] Joes Staal, Associate Member, IEEE, Michael D. Abràmoff, Member,
IEEE, Meindert Niemeijer, Max A. Viergever, Member, IEEE, and
Bramvan Ginneken, Associate Member, IEEE, " Ridge-Based Vessel
Segmentation in Color Images of the Retina", IEEE transactions on
medical imaging, vol. 23, no. 4, April 2004.
[16] Li Chen, IEEE Member, Xiao-Long zhang, "Feature-based image
registration using bifurcation structures", Matlab Central.