| Resum: |
With the rise of the Internet, remote verification of identity is an increasingly important part of modern life. From online banking systems to personal data storage to software as a service, most aspects of modern life require identity verification. Traditional authentication systems rely on the possession of a token, generally a password or smartcard. Token-based identity transactions are relatively easy to repudiate since unauthorized persons may possess the token. A system that can guarantee a user's presence during authentication would greatly enhance the non-reputability of these transactions. Biometrics can provide this strong link between users and their identities. By measuring and comparing a feature of the user, we can increase the assurance that the user is present during authentication. Fingerprint biometrics are increasingly used for identity verification. However, these require a careful balance of accuracy and privacy that is missing in many implementations. This dissertation describes a new biometric matching system, the protection of an existing data-type, and a model for matching security with error correction codes. My research develops the Vaulted Verification (VV) system into Vaulted Fingerprint Verification (VFV) by implementing VV on a fingerprint minutia triangle representation [1]. Triangle representation contains much information that enhances the accuracy of the system. VFV matcher requires no order or relation between the minutia triangles. VFV allows for key exchange and remote authentication using the challenge response protocol. Protected biometric template is used to preform the authentication. Privacy and security of the user's biometric data is preserved through multiple levels of protection. First, the system uses a protected transmission protocol to transmit the authentication token. Second, minutia triangles are difficult to invert. Third, VFV is compatible with protected minutia data types. VFV is built on blocks containing several minutia triangles. Selecting several minutia triangles within a block provides tolerance to common errors in fingerprint images. The blocks are permuted to store arbitrary data, such as encryption keys or an authenticator challenge. The data is combined with an error correcting code to provide tolerance to inter-image errors in fingerprint minutia. VFV is fully compatible with protected biometric data-types. This is demonstrated by including a protected minutia descriptor, Protected Minutia Cylinder Code (PMCC) [2]. PMCC is known for its ability to enhance the accuracy of matching fingerprint minutia while being difficult to invert. Augmented VFV features with PMCC enhance the accuracy of the system. A modification of PMCC is developed in this dissertation to enhance the privacy of the system. The PMCC's within a minutia triangle are XORed together. The XOR procedure greatly enhances the non-invertiblity of PMCC, while having a small impact on VFV accuracy. Due to the importance of error correcting codes (ECC) in VFV, a model of security with ECC is developed. It is used to identify non-trivial potential attacker uses of ECC bits. |
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