Reinforcing Social Network Security with Face Biometrics and Deep Learning

A Reinforcing Social Network Security with Face Biometrics and Deep Learning depicts the design and development of an innovative face recognition system with a novel graphical-based password. Face recognition systems become increasingly pivotal in authentication processes to improve both accuracy and scalability. The system integrates advanced deep learning techniques with reinforcement learning frameworks, allowing the system to learn from interactions and improve over time. The architecture of Deep Learning algorithms is used to design efficient facial features while adapting to user behaviors and environmental variations. The CNN is used for face recognition and analysis by learning features from facial images and YOLOv8 is used for real-time face detection in live streams for security. OpenCV is used for image processing tasks such as capturing frames from webcams and preprocessing face images. Processing power CPU provides sufficient power to run the deep learning models in real-time for facial detection.