a fingerprint bio-cryptosystem to mitigate fingerprint uncertainity in

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    A FINGERPRINT BIO-CRYPTOSYSTEM TO

    MITIGATE FINGERPRINT UNCERTAINITY IN

    MODIFIED VORONOI NEIGHBOR

    STRUCTURES

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    INTRODUCTION

    Machine learning: deals with the construction and study ofsystems that can learn from data, rather than follow onlyexplicitly programmed instructions

    Pattern recognition:

    The assignment of a physical object orevent to one of several pre-specified categories

    A patternis an object, process or event that can be given aname.

    A pattern class(or category) is a set of patterns sharingcommon attributes and usually originating from the samesource.

    . 2

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    CONT

    During recognition(or classification) given objects are assigned to

    prescribed classes

    A classifieris a machine which performs classification

    Examples of application

    Biometrics

    Military Applications

    Diagnostic systems

    Optical character recognition

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    CONT

    BIO-CRYPTOGRAPHY

    Bio-cryptography combines cryptography with bio-metrics

    Bio-cryptosystems provide security

    i)securing the cryptographic key using biometric features

    ii)Generating the cryptographic key directly from biometrics

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    OBJECTIVE

    To design an alignment-free bio-cryptosystem based on modified

    voronoi neighbor structures

    To provide local structural stability and distortion insensitivity.

    The proposed system is able to provide good security and high

    recognition rate.

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    RELATED WORKS

    K.Nandakumar,A.K.Jain,S.Pankanti,Fingerprint based fuzzy

    vault: implementation and performance,IEEE transactions on

    Information Forensics and security,Pg no:744-757,Vol:2,2007

    Problem: To protect the fingerprint template of a user typicallystored in a database or a smart card

    Solution: Fuzzy vault scheme protects both secret key and biometric

    template

    Disadvantage: Alignment of query fingerprint with template is a

    challenging task

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    W.Yang,J Hu,S.Wang,A Delaunay Triangle-Based Fuzzy

    Extractor for Fingerprint Authentication, Proceedings of the

    IEEE 11thInternational conference on trust, security and Privacy in

    Computing and Communications,Pg no:66-70,2012

    New scheme: Registration-free Delaunay triangle based fuzzy

    extractor

    Fuzzy extractor consists of two primitives:

    1.Secure sketch

    2.Fuzzy Extractor

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    K.Xi,J.Hu,F.Han,An alignment free fingerprint fuzzy extractor

    using near equivalent dual layer structure check algorithm,

    Proceedings of the IEEE Conference on Industrial Electronics and

    applications,Pp:1040-1045,2011

    Problem: Feature alignment, Verification Accuracy, Information

    Accuracy

    Solution: Minutia local structure features: Dual layer structure check

    New fuzzy extractor scheme based on NeDLSC

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    Wencheng Yang et al,Analignment free bio-cryptosystem based

    on modified voronoi neighbor structures,ELSEVIER,1309-

    1320,Vol no:47,2013

    Problems: Fingerprint uncertainty caused by distortion ,rotation andpre-alignment

    Solution:Voronoi neighbor structures provide local structural

    stability and distortion insensitivity

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    SYSTEMMODEL

    Preprocessing &

    minutiae

    extraction

    Preprocessing

    &minutiae

    extractionPreprocessing &

    minutiae

    extraction

    Formation of VNSs

    Generation of modified

    VNSs

    Generation of fixed-length bit-

    string representations

    Encrypted Matching

    Template

    fingerprint

    Query

    Fingerprint

    Match/Non-

    match

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    Orientation fieldestimation Fingerprint regionlocalizationSmoothing filter

    Minutia

    ExtractionThinning Ridge Detection

    Fig: Flowchart of Pre-processing and Minutia Extraction

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    Minutia

    Extraction

    Modified

    VNSs3D array

    Template

    features

    Secure

    Sketch

    Sketched

    data set

    Secure

    Sketch(SS)

    B_VNST

    i

    SS(B_VNS )T

    i

    Secret

    Key

    Hash

    Key Binding

    Polynomial

    Fig :The Encoding Stage

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    Minutia

    Extraction

    ModifiedVNSs

    3D array Queryfeatures

    Sketched

    data set

    Recover RecoveredFeature set

    Secret Key

    Recover

    module

    SuccessRec(B_VNSQj ,SB_VNSTi )

    FailNext decoding attempt

    B_VNSQ

    j

    SB_VNST

    i

    Key

    Retrieving

    Polynomial

    reconstruction

    Fig: The decoding Stage13

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    TOOLS

    Language: Java

    JDK 8

    Netbeans 8-IDE

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