Private Video Foreground Extraction through Chaotic Mapping based Encryption in the Cloud
Xin Jin∗ , Kui Guo , Chenggen Song , Xiaodong Li, Geng Zhao , Jing Luo , Yuzhen Li, Yingya Chen, Yan Liu,and Huaichao Wang
Recently, storage and processing large-scale visual media data are being outsourced to Cloud Data Centres (CDCs). However, the CDCs are always third party entities. Thus the privacy of the users’ visual media data may be leaked to the public or unauthorized parties. In this paper we propose a method of privacy preserving foreground extraction of video surveillance through chaotic mapping based encryption in the cloud. The client captures surveillance videos, which are then encrypted by our proposed chaotic mapping based encryption method. The encrypted surveillance videos are transmitted to the cloud server, in which the foreground extraction algorithm is running on the encrypted videos. The results are transmitted back to the client, in which the extraction results are decrypted to get the extraction results in plain videos. The extraction correctness in the encryption videos is similar as that in the plain videos. The proposed method has several advantages: (1) The server only learns the obfuscated extraction results and can not recognize anything from the results. (2) Based on our encryption method, the original extraction method in the plain videos need not be changed. (3) The chaotic mapping ensure high level security and the ability to resistant several attacks.