Synergising fingerprint biometrics and cryptography for improved authentication

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With the advances in Information Technology (IT) there has been an increase in threats to the communication systems and their assets. One of the most important issues of all Internet Protocol (IP) networks that integrate wireless and wired technologies is the applicability and performance of the electronic identification and authentication methods. These schemes employ a variety of technologies of different degrees of security. Cryptography and biometrics are identified as two of the most important aspects of digital security environments. Biometrics technology nowadays is typically considered a security necessity, tightly coupled with the foundation of highly secure identification and authentication solutions. Also, a biometric system itself is vulnerable to a number of threats. A critical issue in biometric system is to protect the template of a user which is usually stored in a database or a smart card. While cryptography is a powerful tool to accomplish information security, one of the main challenges in crypto systems is to maintain the secrecy of the cryptographic keys. The fuzzy vault construct is a biometric cryptosystem that secures both the secret key and the biometric template by binding them within a cryptographic framework. The ability to work with the fuzzy data which is common in biometric systems makes this method a promising solution for biometric cryptosystems. In many applications, fingerprint has been chosen as a core biometric for the fuzzy vault construction. In this thesis, fingerprint has been selected for further study due to its maturity in terms of availability, uniqueness, permanence, feasibility, ease of use and acceptance. It is expected to address some of the limitations in fingerprint fuzzy vault construction by modifying this structure. Finally, the main contribution of this work is two-fold as follows: 1. An exhaustive review study of the current state of the art in utilising biometrics and cryptography for authentication, more specifically for fingerprint biometric. 2. Proposing a novel method in fingerprints curve extraction which would improve upon current methods on computational load while preserving the required precision. Fingerprints curve extraction is a vital function for both fingerprint classification and extracting the so-called “helper data”. Helper data are required in fuzzy vault implementation.
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