Liveness Detector for Face Recognition System Fake Vs Real

facial recognition systems are increasingly deployed for identity verification and security, but they remain vulnerable to spoofing attacks using photographs, videos, or 3D masks. To address these challenges, a liveness detection mechanism is critical to distinguish between real, live human faces and spoofed or fake inputs. This paper presents a liveness detection framework integrated with a facial recognition system, utilizing techniques such as eye-blink detection, facial micro- movements, texture analysis, and 3D depth estimation. The proposed system aims to enhance the security of face-based authentication by rejecting spoofed attempts in real-time, with minimal latency and high accuracy. Experimental results demonstrate the effectiveness of the approach across a variety of spoofing scenarios, including printed photos and digital screen replays. Face recognition is a widely used biometric approach. Face recognition technology has developed rapidly in recent years and it is more direct, user friendly and convenient compared to other methods. But face recognition systems are vulnerable to spoof attacks made by non-real faces. It is an easy way to spoof face recognition systems by facial pictures such as portrait photographs. And face forthe development of technology recently, almost all universities in Indonesia have implemented online attendance. An online attendance system using facial recognition is a technology that is able to identify a person’s face from a digital image