Application of Machine Learning in Biometric Authentication
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Abstract
Biometric authentication is a popular approach for information and device security in the new normal era, in particular for transactions such as accessing devices and buildings, online purchasing of goods and services. The clear user benefits are the lessening of touch with high accuracy. However, machine learning technology is essential for biometric authentication in big data environments as it can reduce the hassle of modifying the program and increase the intelligent of the system. This paper was composed to allow users to understand the operation of biometric authentication system as well as to present advances in integrating machine learning into biometric authentication systems. The analysis of strengths and weaknesses of 3 are widely used biometrics: fingerprints, iris and faces was presented. The obvious merit is users have sufficient understanding of the authentication technology so that they can choose security technology appropriately and effectively.
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