Abstract
Face biometric researchers have had a lot of success over the past 62 years. Face recognition technology has been widely employed in both commercial and governmental applications, including mobile, banking, and surveillance systems. Though, the facial recognition system's ability to survive an uninvited attacker is a crucial issue. Face recognition software is susceptible to fake images and video attacks. Anti-spoofing solutions are useful in these situations for thwarting these attacks. The biometric community as a whole, including researchers, developers, and retailers, has spent the last ten years working on difficult projects to create a more precise defence against spoofing attacks. Despite numerous face anti-spoofing or liveness detection techniques being put out, the problem has not been addressed since it is challenging to identify the features and techniques for spoof assaults. This paper's objective is to present a thorough analysis of antispoofing techniques. The study came to the conclusion that in order to increase the system's security, computational efficiency, and dependability, it is necessary to provide more generalized methods for the detection of unanticipated spoofing assaults.
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