This research presents a novel approach to face recognition by integrating Local Binary Pattern (LBP) feature extraction with Galois/Counter Mode (GCM) cryptographic techniques. Face recognition plays a significant role in various domains, including security and biometrics. The LBP algorithm is employed to capture local texture information from facial images, enhancing robustness against lighting variations and facial expressions. On the other hand, GCM is utilized to provide secure data encryption during transmission, ensuring both confidentiality and authenticity. The proposed system demonstrates promising results in face recognition accuracy while maintaining the utmost data security, making it suitable for real-world applications where robust and secure identity verification is crucial. This fusion of LBP and GCM presents a reliable and efficient solution to address the challenges faced in modern face recognition systems.