Principal Component Analysis and Data Encryption Model for Face Recognition System

Face recognition is a biometric technique that uses a computer or machine to facilitate the recognition of human faces. The advantage of this technique is that it can detect faces without direct contact with the device. In its application, the security of face recognition data systems is still not given much attention. Therefore, this study proposes a technique for securing data stored in the face recognition system database. It implements the Viola-Jones Algorithm, the Kanade-Lucas-Tomasi Algorithm (KLT), and the Principal Component Analysis (PCA) algorithm by applying a database security algorithm using XOR encryption. Several tests and analyzes have been performed with this method. The histogram analysis results show no visual information related to encrypted images with plain images. In addition, the correlation value between the encrypted and plain images is weak, so it has high security against statistical attacks with an entropy value of around 7.9. The average time required to carry out the introduction process is 0.7896 s.