<![CDATA[Facial recognition has been widely adopted by many systems as authentication. However, relying on facial photos for authentication is insufficient, as these can be manipulated using printed or digital photos. One method that can be used to prevent this is to integrate face recognition with liveness detection. In this research, face recognition and liveness detection are implemented using a Convolutional Neural Network (CNN) because CNN has the ability to process and extract features from photos effectively. There are two types of datasets used, namely CelebA-Spoof for liveness detection and lfw-deepfunneled for face recognition. The face recognition model achieved good accuracy and loss results of 0.9153 and 0.0514, very promising. Meanwhile, the liveness detection accuracy and loss were 0.8633 and 0.7166.]]>
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