This paper presents a scheme of deep convolution network for image hashing authentication． First，the AlexNet model of deep convolution network is constructed and the given network performance is achieved through training． Then， the trained network is used to extract image features and generate image-hashing series for content authentication． The experimental results show that in comparison with other methods，the proposed method has a higher discrimination and an acceptable robustness against content-preserving operations such as random attack， rotation，JPEG compression，and additive Gaussian noise． Receiver operating characteristics ( ROC) curve comparison demonstrates that the proposed method is able to attain a desirable compromise between the robustness and discrimination．