A privacy-sensitive and secure face recognition system has been developed that provides a reasonable balance between the accuracy, safety and usability. It starts with detecting faces with a quick technique known as Haar Cascade, which detects faces in a picture as quick as possible. It then applies the Local Binary Patterns Histogram (LBPH) method to extract important information of a face. LBPH is simple and it is effective in face recognition, ven when lighting or expressions are altered. To guarantee the privacy of the users, the facial features are translated into special templates, which can be canceled or changed in case of necessity, like the reset of a password. These templates do not preserve the original face image, thus the original data is not compromised. The templates are randomization and locked with strict encryption prior to saving them by using the XChaCha20-Poly1305 algorithm before locking them in a secure manner. This prevents the information being leaked and tampered with. When a person has to be identified, the system compares the encrypted templates with a match. Such a setup assists in averting hacking, identity theft, and face attacks. However, even in case of a stolen data, this cannot be used to recreate the face of a person. This system is a privacy-oriented, secure, and intelligent method of identifying faces, and thus it can be used by both small and large applications.