Contemporary protocols in the TCP/IP suite may be very vulnerable to spoofing attacks when extra precautions are not taken to verify the identity. There are several ways to spoof the facial recognition such as using photograph, three-dimensional (3D) model, and video clip of a valid user. Studies show that there have been significant improvements in detecting photograph and 3D model spoofing. However, there is no such improvement in detecting video spoofing. Recent studies also show that liveliness monitoring using the facial features has potential to improve security, especially in biometric systems. In this paper, an efficient method to detect video spoofing using liveliness monitoring is introduced. An eye blinking password system using ultrasonic range sensing module is developed for liveliness detection of the users. In the proposed system, local facial features like eye blinking and chin movement pattern are used via a real-time generic web-camera. The system is tested by conducting experiments using 20 valid users and 100 different users' appearances. According to the experimental results, the proposed system achieves 100% face recognition accuracy and 100% liveliness detection performance.