aspg-41-3488-1792222955 20261017074235 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Metaheuristic Optimization Review MOR 3066-280X 2025 3 1 El-Sayed M. El-kenawy School of ICT, Faculty of Engineering, Design and Information & Communications Technology (EDICT), Bahrain Polytechnic, PO Box 33349, Isa Town, Bahrain Anis Ben Ghorbal Department of Mathematics and Statistics, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia. FRT is acknowledged as one of the successful advancements of biometric applications in security, surveillance, health care and innovative solutions. More so, the past decade has seen improvements in deep learning, pre-trained Neural Network Convolutional Neural Networks (CNNs), and combining methods such as ensembles, which have highly improved the FRT's Accuracy and efficiency. Nonetheless, several issues remain – facial expression, illumination, demographic biases or adversarial and backdoor threats. Such limitations require new approaches and tools to enhance FRT's reliability and ethical use. The current review also presents ethical concerns and the social consequences of using FRT. 2025 19 23 3488 https://creativecommons.org/licenses/by/4.0/ 10.54216/MOR.030105 https://americaspg.com/journal/41/article/3488 https://americaspg.com/storage/articles/manuscripts/01KXBSKQXT5CTXBZFGKJ2D5P8Q.pdf