Biometric Template Protection - NIST Visual Image Processing Group

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How to Assess <strong>Template</strong> <strong>Protection</strong>§Definition of security:§ Let A(AD, PI)=[M’, PI’] be a reconstruction function, where PI’=PIR(M’, AD).T A is the computational time required in one reconstruction andn is the average number of reconstructions needed to get a [M’, PI’] suchthat PIC(PI,PI’)=1 for a positive authentication result§ A template protection algorithm is (Τ, ε)- secure, if for all AT A ≥ Τlog 2 n ≥ ε§Definition of privacy:§Let A(AD, PI)=[M´, PI´] be a reconstruction function, where PI´=PIR(M´, AD). T Ais the computational time required in one reconstruction; for a given threshold t,n is the average number of reconstructions needed to get a [M´, PI´] such thatfor a distance function dist(M, M´)
Assessment of Different Protected Systems§ The fuzzy commitment scheme for 3D face recognition§ The fuzzy commitment scheme for iris recognitionEncoderDecoderKeystreamGeneratorSecretSErrorCorrectionEncoderCXORWXORC’ErrorCorrectionDecoderS’XX’§ The fuzzy vault algorithm for fingerprint recognitionMinu%ae(Informa%on.A Privacy and Security Evaluation Framework for TP| Xuebing Zhou |Gaithersburg, March 09, 201212
Page 1 and 2: A Generalized Framework forPrivacy
Page 3 and 4: Biometric Systems§ Privacy and sec
Page 5 and 6: Biometric Template ProtectionA Priv
Page 7 and 8: Biometric Template ProtectionPT1PT2
Page 13 and 14: State of the Art of Template Protec
Page 15 and 16: How to Assess Template Protection§
Page 17 and 18: How to Assess Template ProtectionEv
Page 19: How to Assess Template Protection§
Page 23 and 24: Assessment of Different Protected S
Page 25 and 26: Conclusions§ The framework is usef
Page 27 and 28: References§ Zhou, Xuebing: “Priv

Biometric Template Protection - NIST Visual Image Processing Group

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