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Secure smartcardbased fingerprint authentication
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Proceedings of the 2003 ACM SIGMM workshop on Biometrics methods and applications table of contents
Berkley, California
SESSION: Oral II table of contents
Pages: 45 - 52  
Year of Publication: 2003
ISBN:1-58113-779-6
Authors
T. Charles Clancy  University of Maryland, College Park
Negar Kiyavash  University of Illinois, Urbana-Champaign
Dennis J. Lin  University of Illinois, Urbana-Champaign
Sponsor
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
Publisher
ACM  New York, NY, USA
Bibliometrics
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ABSTRACT

In this paper, the fundamental insecurities hampering a scalable, wide-spread deployment of biometric authentication are examined, and a cryptosystem capable of using fingerprint data as its key is presented. For our application, we focus on situations where a private key stored on a smartcard is used for authentication in a networked environment, and we assume an attacker can launch o -line attacks against a stolen card.Juels and Sudan's fuzzy vault is used as a starting point for building and analyzing a secure authentication scheme using fingerprints and smartcards called a figerprint vault. Fingerprint minutiae coordinates mi are encoded as elements in a nite eld F and the secret key is encoded in a polynomial f(x) over F[x]. The polynomial is evaluated at the minutiae locations, and the pairs (mi, f(mi)) are stored along with random (ci, di) cha points such that di ≠ f(ci). Given a matching fingerprint, a valid user can seperate out enough true points from the cha points to reconstruct f(x), and hence the original secret key.The parameters of the vault are selected such that the attacker's vault unlocking complexity is maximized, subject to zero unlocking complexity with a matching fingerprint and a reasonable amount of error. For a feature location measurement variance of 9 pixels, the optimal vault is 269 times more difficult to unlock for an attacker compared to a user posessing a matching fingerprint, along with approximately a 30% chance of unlocking failure.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
2
 
3
Blahut, R. Algebraic Codes for Data Transmission. Cambridge University Press, 2003.
 
4
Blahut, R. Modem Theory: An Introduction to Telecommunications. Cambridge University Press, preprint.
 
5
Bleichenbacher, D., and Nguyen, P. Q. Noisy polynomial interpolation and noisy chinese remaindering. Advances in Cryptology, EUROCRYPT 2000.
 
6
Davida, G., Frankel, Y., and Matt, B. On enabling secure applications through o -line biometric identification. IEEE Symposium on Privacy and Security, 1998.
 
7
 
8
 
9
Jaeger, H., and Nagel, S. Physics of granular states. Science 255, 1524 (1992).
 
10
Juels, A., and Sudan, M. A fuzzy vault scheme. ACM Conference on Computer and Communications Security, CCS 2002.
11
 
12
 
13
 
14
Kuhn, M., and Anderson, R. Tamper resistance: A cautionary note. Workshop on Electronic Commerce, USENIX 1996.
 
15
Kummerling, O., and Kuhn, M. Design principles for tamper-resistant smartcard processors. Workshop on Smartcard Technology, USENIX 1999.
 
16
 
17
Massey, J. L. Shift register synthesis and bch decoding. IEEE Transactions on Information Theory 15, 1 (1969), 122--127.
18
 
19
 
20
Osterberg, J., Parthasarathy, T., Raghavan, T., and Sclove, S. Development of a mathematical formula for the calculation of fingerprint probabilities based on individual characteristics. Journal of the American Statistical Association 72 (1977), 772--778.
 
21
 
22
Sclove, S. The occurance of fingerprint characteristics as a two-dimensional process. Journal of the American Statistical Association 74 (1979), 588--595.
 
23
Steinhaus, H. Mathematical Snapshots, 3 ed. Dover, 1992.
 
24
Vandenwauver, M., Govaerts, R., and Vandewalle, J. Overview of authentication protocols: Kerberos and sesame. IEEE Carnahan Conference on Security Technology 1997, pp. 108--113.
 
25
Verifinger. Neurotechnologija ltd. http://www.neurotechnologija.com.
 
26
Ylonen, T. Ssh secure login connections over the internet. Security Symposium, USENIX 1996, pp. 37--42.

CITED BY  10

Collaborative Colleagues:
T. Charles Clancy: colleagues
Negar Kiyavash: colleagues
Dennis J. Lin: colleagues