A Concise Review on the Emerging Field of In-Ear Acoustics Biometrics User Authentication

User Authentication have been for long a well-known standard practice in securing personal and commercial applications be they hardware and/or software solutions to mitigate against potential risks revolving around data privacy and access control. In the times past and even the present moment, the use of password and simple logins persisted. However, the evolving field of smart computing including the rapid growth of advanced sensor based technologies has led to the rise of biometric-capable user authentication systems. These systems add an extra layer of security to the standard simple authenticators including the use of one or more biometric traits as face, finger or even voice etc. However, notwithstanding this additional benefit, the existing biometric traits pose a number of issues that mitigate a successful use of biometrics-based user authentication systems. In this study, we present the emerging field of in-ear acoustics based biometrics as a candidate and more efficient user authentication system. We conduct our reviews on the basis of their adopted approach, strengths and weaknesses with particular emphasis on the role of Machine Learning (ML) in the person authentication or identification process.