Security is a global concern that requires the attention of governments, stakeholders, corporations, and individuals to establish effective protection mechanisms. Installing surveillance systems for detection and monitoring is crucial. However, facial recognition becomes increasingly difficult due to lighting variation, poses of the face, and occlusion caused by face mask. This paper introduces face detection to enhance national security and promote economic development in Nigeria. The system is designed using background subtraction for denoising and YOLO for detection, and the new face detection and recognition algorithm is implemented in Python. The proposed system underwent evaluation, and the experimental results, based on performance metrics, demonstrate that the algorithms significantly improve processing time with an accuracy of 79.3%. Additionally, the proposed work offers an accurate and effective method for monitoring and detecting moving objects, making it suitable for applications where security is a primary concern.