Abstract
Biometric identification systems are principally related to the information security as well as data protection and encryption. The paper proposes a method to integrate biometrics data encryption and authentication into error correction techniques. The normal methods of biometric templates matching are replaced by a more powerful and high quality identification approach based on Grobner bases computations. In the normal biometric systems, where the data are always noisy, an approximate matching is expected; however, our cryptographic method gives particularly exact matching.
Highlights
Digital data sent over communication channels are subject to distorting as a result of various circumstances such as electromagnetic fluctuations
The last example is the biometric feature vectors made of the attributes of the individuals which are noisy by nature
Even though many commercial and academic systems for biometrics identification are working out, the considerable number of publications on this domain states the necessity for extensive research for the sake of obtaining better performance and enhancing the reliability of such systems
Summary
Digital data sent over communication channels are subject to distorting as a result of various circumstances such as electromagnetic fluctuations. Since the binary feature vectors of biometric templates acquired from the same person are most probably different from each other, it is necessary to detect and rectify the difference between the data acquired in the enrollment and verification steps [14] [15]. This correction takes the place of the normal templates matching in present biometric systems. In this work we develop a new biometric authentication algorithm that is based on the data contained in biometric templates and on a randomly selected codeword from an LDPC code. The main obstacle to our algorithm is that the computations of Grӧbner bases are expensive, and (in non-commutative algebras) are not guaranteed to stop [22]
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