Abstract

In response to the increased demand for more effective authentication methods, the usage of biometric authentication to secure systems against unwanted access has grown. Because of the recent COVID-19 pandemic outbreak, any direct physical contact with the system should be avoided. Furthermore, current authentication systems lack the necessary security features, making them vulnerable to cyber risks such as forgery by unethical employees and unauthorized users. The goal of this paper is to investigate the existing biometric authentication systems and propose the best security models to overcome the weaknesses of existing technologies. The study employed mixed methodology, which was qualitative and quantitative in nature and relied on primary and secondary sources of data. The researcher collected the data from a population of 300 staff of Mount Kenya University with a sample size of 169 respondents. The R2 value on the relationship between the studied dependent and independent variables was R2 = 0.792 showing a good fit of the model since is greater than 50% of the test item used in the case study. Therefore the study recommends that institutions to implement a contactless biometric system to eliminate physical contact and use multimodal system that will help overcome the existing challenges associated with unimodal systems. There are still gaps for future researchers where they need to focus on the various decision algorithms that are best efficient in verifying users before they are authenticated in the system.

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