COMPARATIVE ANALYSIS OF MULTI-FACTOR AUTHENTICATION USING KEYSTROKE DYNAMICS AND FACIAL RECOGNITION WITH GAIT BIOMETRICS

Abstract

With the threats of cybersecurity growing, authentication methods need to advance to ensure good security without compromising user convenience. Conventional methods of authentication like passwords and PINs are prone to compromise and social engineering attacks. To counter these limitations, biometric authentication has been introduced as a promising solution that can improve security through the use of distinctive physiological and behavioral characteristics of users. Of the different biometric modalities, keystroke dynamics and facial recognition have shown considerable promise for multi-factor authentication (MFA) systems. Behavioral biometrics, including gait recognition, have also attracted attention as a substitute or supplementary authentication factor. This chapter discusses the relative efficacy of keystroke dynamics and facial recognition vis-a-vis gait biometrics in multi-factor authentication systems, including their strengths, weaknesses, and potential uses.

Biometric authentication is typically classified as either physiological or behavioral biometrics. Physiological biometrics comprise fingerprints, iris scanning, and face recognition, while behavioral biometrics involve typing, voice, and gait patterns. Keystroke dynamics scan the way and pace at which an individual types, offering extra security within authentication systems. Likewise, face recognition systems record and scan facial details to confirm the identity of a user. Gait recognition, however, assesses a person's gait, providing a non-intrusive and contactless authentication technique. Both modalities possess unique strengths and weaknesses, requiring comparative analysis to ascertain the best method of securing digital systems.