A comparative study on face spoofing attacks

In the last 57 years, face biometrie researchers have achieved many successes. Face recognition systems have been extensively used in government as well as commercial applications such as mobile, banking and surveillance systems etc. In the last 10 years, the whole biometric community such as researchers, developers, and retailers have worked on challenging tasks to develop a more accurate protection method against spoofing threats. The face spoofing attacks affect high-security field in the companies, government sectors, rising small and medium sized endeavors. Although several face antispoofing or liveness detection methods have been proposed, the issue is still unresolved due to difficulty in finding the features and methods for spoof attacks. Recently it has been shown that the traditional face biometric techniques are more vulnerable to spoofing attacks, so entire research community required to concentrate more to resolve solutions against spoofing attacks. The goal of this paper is to provide a detailed study of antispoofing methodologies and evaluation of databases. The study concluded that there is a need to provide more generalized algorithms for detection of unpredictable spoofing attacks in order to make the system more secure, computationally efficient and reliable.