A Novel Video Encryption Method Based on Faster R-CNN

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. Keywords—video encryption; faster R-CNN; the ROI of video

[1]  Fei Peng,et al.  A Perceptual Encryption Scheme for HEVC Video with Lossless Compression , 2017, ICCCS.

[2]  Ayman Alfalou,et al.  Simultaneous compression and encryption of color video images , 2015 .

[3]  Linlin Wang,et al.  Image/video encryption using single shot digital holography , 2015 .

[4]  Jian Sun,et al.  Convolutional feature masking for joint object and stuff segmentation , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[5]  KokSheik Wong,et al.  Region-of-interest encryption in HEVC compressed video , 2016, 2016 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW).

[6]  M. García-Martínez,et al.  Pseudo-random bit generator based on multi-modal maps , 2015 .

[7]  Dumitru Erhan,et al.  Scalable Object Detection Using Deep Neural Networks , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[8]  Majid Naderi,et al.  Encryption of Video Main Frames in the Field of DCT Transform Using A5/1 and W7 Stream Encryption Algorithms , 2014 .

[9]  Yuling Liu,et al.  A ROI-based reversible data hiding scheme in encrypted medical images , 2016, J. Vis. Commun. Image Represent..

[10]  Moncef Gabbouj,et al.  Perceptual Encryption of H.264 Videos: Embedding Sign-Flips Into the Integer-Based Transforms , 2014, IEEE Transactions on Information Forensics and Security.

[11]  A Lijiya,et al.  Transform Domain Video Steganography Using RSA, Random DNA Encryption and Huffman Encoding , 2017 .

[12]  Xing-yuan Wang,et al.  A new image alternate encryption algorithm based on chaotic map , 2014, Nonlinear Dynamics.

[13]  Slavko Gajin,et al.  An efficient mechanism of cryptographic synchronization within selectively encrypted H.265/HEVC video stream , 2017, Multimedia Tools and Applications.

[14]  Martin Fleury,et al.  Transparent encryption with scalable video communication: Lower-latency, CABAC-based schemes , 2017, J. Vis. Commun. Image Represent..