A Comprehensive Overview on Biometric Authentication Systems using Artificial Intelligence Techniques

Abstract

Biometric authentication is becoming more prevalent as it allows consumers to authenticate themselves without entering a physical address or a personal identification number. Thus, a simple finger gesture or a glance at a camera can still prove one's identity. In this review, we explain in detail how the concept of authentication and the various types of biometric techniques is used for user identification. Then, we discuss the various ways these techniques can be combined to create a truly multimodal authentication system. For a more organized approach, our overview is classified into two main categories based on human biometric traits. First, the physiological traits include fingerprint, facial, iris/retina, hand, and fingervein. Second, the behavioral traits includes voice, signature, and keystroke recognition systems. Finally, we offer a comprehensive comparison of selected methods and techniques and focus on three criteria: algorithms, merits, and drawbacks. Based on this comparison, we provide insight into our future research in iris recognition, by which we combine several artificial intelligence algorithms to develop our system.