eBiometrics: an enhanced multi-biometrics authentication technique for real-time remote applications on mobile devicesDate:2021-09-17
Regional fingerprint liveness detection systems and methods
With the development of the times, financial shared service center has become more and more diversified and complex and the traditional financial system cannot meet the needs of enterprises. Only by providing services anytime and anywhere can we be invincible. In order to reduce costs and improve efficiency, financial institutions deploy biometric technology in various service channels to ensure user authentication and improve the security and timeliness of business processing. Therefore, this article puts forward the application of biometrics in financial shared service center. In order to verify the advantages of biometric technology, this paper analyzes the efficiency and management cost of biometric technology after it is put into use, and tests the cost change of an enterprise for four consecutive years and the change of personnel age for three consecutive years. Through this analysis, it is concluded that the input of biometric technology is conducive to the control of enterprise cost and the adjustment of personnel structure. In order to further the feasibility of biometric technology, this paper compares the data before and after the reform of enterprise financial system. The results show that the efficiency of financial business processing has increased from 5.8 days to 0.41 days, and the efficiency has increased by 14.15 times, which is in the international high level, and the financial shared service center is more intelligent and efficient. Through the analysis, the research in this paper has achieved ideal results and made a contribution to the application of biometric technology in financial shared service center.
This paper investigates liveness detection techniques in the area of eye movement biometrics. We investigate a specific scenario, in which an impostor constructs an artificial replica of the human eye. Two attack scenarios are considered: 1) the impostor does not have access to the biometric templates representing authentic users, and instead utilizes average anatomical values from the relevant literature and 2) the impostor gains access to the complete biometric database, and is able to employ exact anatomical values for each individual. In this paper, liveness detection is performed at the feature and match score levels for several existing forms of eye movement biometric, based on different aspects of the human visual system. The ability of each technique to differentiate between live and artificial recordings is measured by its corresponding false spoof acceptance rate, false live rejection rate, and classification rate. The results suggest that eye movement biometrics are highly resistant to circumvention by artificial recordings when liveness detection is performed at the feature level. Unfortunately, not all techniques provide feature vectors that are suitable for liveness detection at the feature level. At the match score level, the accuracy of liveness detection depends highly on the biometric techniques employed.
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