Biometrics and ID Management: COST 2101 European Workshop, by Andrzej Drygajlo (auth.), Claus Vielhauer, Jana Dittmann,

By Andrzej Drygajlo (auth.), Claus Vielhauer, Jana Dittmann, Andrzej Drygajlo, Niels Christian Juul, Michael C. Fairhurst (eds.)

This publication constitutes the completely refereed complaints of the fee 2101 overseas Workshop, BIOID 2011, held in Brandenburg (Havel), Germany, in March 2011.
The 25 revised complete papers awarded have been conscientiously reviewed and chosen from quite a few submissions and are accomplished through an creation on expense. The papers are prepared in topical major sections on thought and platforms, handwriting authentication, speaker authentication, face attractiveness, multibiometric authentication, and on biometrics and forensics.

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Extra resources for Biometrics and ID Management: COST 2101 European Workshop, BioID 2011, Brandenburg (Havel), Germany, March 8-10, 2011. Proceedings

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Proof: The random variable m(a, B n ) can be expressed as m(a, B n ) = 1 n m(0, Bt ) + t∈T0 1 n m(1, Bt ), t∈T1 where m(a1 , B1 ), . . , m(an , Bn ) are independent random variables. Therefore, nE[ m(a, B n ) ] = E[ m(0, Bt ) ] + t∈T0 and n2 Var[ m(a, B n ) ] = E[ m(1, Bt ) ] t∈T1 Var[ m(0, Bt ) ] + t∈T0 Var[ m(1, Bt ) ], t∈T1 where T0 = t ∈ {1, . . , n} : at = 0 , T1 = t ∈ {1, . . , n} : at = 1 . Biometric Authentication Based on Significant Parameters 21 In the Acc case, ⎧ ⎨ −p, with 0, with t ∈ T0 ⇒ m(0, bt ) = ⎩ +p, with ⎧ ⎨ −(1 − p), 0, t ∈ T1 ⇒ m(1, bt ) = ⎩ +(1 − p), probability 1 − ξ − θ, probability ξ, probability θ, with probability 1 − ξ − θ, with probability ξ, with probability θ.

EV ✻ ✻ T ˆ FAR Q 0 μ ˆ V FRR ˆ Q FAR Fig. 3. Examples of Gaussian approximations to the probability distributions of the metric for the p-authentication algorithm Then ˆ V = 1− FRR 2 1 ˆ Q= + FAR 2 1 erf 2 1 erf 2 EV (T )n , EQ (T )n and, if −2(1 − ξ − 2θ)σp < T /σp < 0, then ˆ V ≤ exp −EV (T )n , FRR ˆ Q ≤ exp −EQ (T )n . FAR Corollary. If q0 = q1 = 1/2 and EV (T ) = EFRR , EQ (T ) = EFAR , then, when θ is small, where EFRR ≈ f (EFAR ), √ (− 2EFAR + 2(1 − ξ)σp )2 f (EFAR ) = .

CIS 2005. LNCS (LNAI), vol. 3802, pp. 635–642. : Enhancing security of fingerprints through contextual biometric watermarking. : A Study on Iris Feature Watermarking on Face Data. , Ribeiro, B. ) ICANNGA 2007. LNCS, vol. 4432, pp. 415–423. Springer, Heidelberg (2007) 36 J. H¨ ammerle-Uhl, K. Raab, and A. : A secure protocol for data hiding in compressed fingerprint images. K. ) BioAW 2004. LNCS, vol. 3087, pp. 205–216. : Enhancing security and privacy in biometrics-based authentication systems.

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