Face Detection with Liveness Net

In this modern era, technology plays a vital role in our day-to-day activities. People, be it young or old tend to rely on various smart devices in completing their daily tasks. During the Covid period, the educational institutions, Government offices, banks, industries and others adopted online mode of working. Everything started transforming towards online operations and this increased a need for security. The devices that are involved in this system need to be secured from the people having malicious intentions. Face verification is one such popular method that can be employed to ensure security, nevertheless it is more exposed to the spoofing attacks. One of the methods that can be incorporated in defending against the spoofing attack would be the use of face liveliness detection, commonly known as face spoofing detection. Techniques like machine learning, deep learning and computer vision, their efficient tools have increased the efficiency and effectiveness in face liveliness detection and is more feasible towards the general-purpose usage. The proposed model is developed using CNN and liveness net algorithm. This model enhances the security system by combining the benefits of face verification and face liveliness detection technologies. As an outcome, model provides 97% of accuracy in detecting the real and fake data.