Biometric Authentication Schemes and Methods on Mobile Devices: A Systematic Review

Biometric Authentication Schemes and Methods on Mobile Devices: A Systematic Review

Akon Obu Ekpezu (Cross River University of Technology, Cross River, Nigeria), Enoima Essien Umoh (Cross River University of Technology, Nigeria), Felix Nti Koranteng (University of Education, Winneba, Kumasi Campus, Ghana) and Joseph Ahor Abandoh-Sam (Valley View University, Ghana)
DOI: 10.4018/978-1-7998-3149-5.ch011

Abstract

Due to the sensitivity and amount of information stored on mobile devices, the need to protect these devices from unauthorized access has become imperative. Among the various mechanisms to manage access on mobile devices, this chapter focused on identifying research trends on biometric authentication schemes. The systematic literature review approach was adopted to guide future researches in the subject area. Consequently, seventeen selected articles from journals in three databases (IEEE, ACM digital library, and SpringerLink) were reviewed. Findings from the reviewed articles indicated that touch gestures are the predominant authentication technique used in mobile devices, particularly in android devices. Furthermore, mimic attacks were identified as the commonest attacks on biometric authentic schemes. While, robust authentication techniques such as dental occlusion, ECG (electrocardiogram), palmprints and knuckles were identified as newly implemented authentication techniques in mobile devices.
Chapter Preview
Top

To justify the need for this review, a search for existing systematic reviews on the subject area was conducted. The aim of this was to establish the current status of research summaries done in the subject area.

Guliani et al., (2018), Jagadeesh and Patil (2017) as well as Patil and Gudasalamani (2016) surveyed iris recognition system. In their review, they provided various methods and algorithms used by different researchers and their effect on the performance of iris recognition systems. They explained the evolution of various parameters to enhance the recognition ability of a biometric method and identified the drawbacks and future works. As a tool for electronic transaction authentication and electronic assessment Ojo et al., (2016) and Shunmugam & Selvakumar (2015) discussed uni-modal biometrics and its limitations, they pointed out the need for Multimodal biometrics and also identified Multimodal methods adopted in recent works.

Key Terms in this Chapter

Physiological Biometrics: Is a method for uniquely recognizing an individual using his or her intrinsic physical traits.

Multimodal Biometrics: Is a biometric identification system that uses two or more biometric modalities to uniquely identify an individual.

Biometrics Authentication: A unique, non-duplicable, non-transferable, and automated system that authorizes an individual to access a particular device based on his/her physiological or behavioural characteristics.

Behavioural Biometrics: Is a method for uniquely recognizing an individual using measurable patterns in human activities or actions.

False Reject Rate: Is the measure of the rate at which a biometric security system will incorrectly reject an access attempt by an authorized user.

False Acceptance Rate: Is the measure of the rate at which a biometric security system will incorrectly accept an access attempt by an unauthorized user.

Unimodal Biometrics: Is a biometric identification system that uses a single biometric attribute to uniquely identify an individual.

Complete Chapter List

Search this Book:
Reset