With the rapid development of artificial intelligence, face recognition, as an important part of artificial intelligence, has a tremendous impact on people's lives. This paper aims to improve the accuracy and rapidity of face recognition by using deep learning and cloud computing technology, as well as to provide face recognition service for intelligent security system. Firstly, the Convolutional Neural Network (CNN) is introduced and Large Margin Cosine Loss (LMCL)+Center Loss is proposed as the loss function of CNN to train the face feature extraction model. Then, combined with cloud computing technology, a parallel model training and face recognition implementation scheme are proposed to solve the problems of large amount of data and slow model training faced by face recognition technology. Finally, the face recognition scheme is applied to the intelligent security system of a telecommunications operators, and good results are achieved.