This exploratory paper investigates the building of face recognition system by using Principal Component Analysis (PCA) for intruders detection. Face-detection algorithms focus on the detection of frontal human faces. It is analogous to image detection in which the image of a person is matched bit by bit. Image matches with the image stores in database. Any facial feature changes in the database will invalidate the matching process. The main goal of the system is to automate the process of checking the presence of persons in a room. Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. For increasing the security level we think to implement anomaly detection, the identification of items, events or observations which do not conform to an expected pattern or other items in a dataset.