A Novel Video Encryption Method Based on Faster R-CNN
Lijuan Duan, Dongkui Zhang, Fan Xu, Guoqin Cui · Proceedings of the 2018 International Conference on Computer Science, Electronics and Communication Engineering (CSECE 2018) · 2018
In order to improve the generalization performance of video encryption and reduce the amount of data in video en-cryption, this paper proposes a video encryption on regions of interest (ROI) method based on Faster R-CNN by combining machine learning with information security.The method trains a Faster R-CNN model using the ROI dataset firstly, and then uses the model to extract ROI in the video.Different encryption algorithms are used to encrypt ROI and non-ROI in the video respectively.To overcome the shortcomings of encryption algorithms that can only be used for a specific coded video, a special video encryption method is proposed to encrypt the video with different video coding structure and has better generalization performance.Compared with the encryption method in the video coding process, this method considers the content information of the video fully and has better performance.It can be concluded through experiments that the encryption method in this paper has the characteristics of higher security and less calculation.