Private Video Foreground Extraction through Chaotic Mapping based Encryption in the Cloud(MMM2016)

 Xin Jin 1 , 3 , ∗ , Kui Guo 1 , Chenggen Song 1 , Xiaodong Li 1 ,? , Geng Zhao 1 , Jing Luo 1 , 2 , Yuzhen Li 1 , 2 , Yingya Chen 1 , Yan Liu 1 , 2 , and Huaichao Wang 3

1 Beijing Electronic Science and Technology Institute, Beijing 100070, China, GOCPCCC Key Laboratory of Information Security, Beijing 100070, China

2 Xidian University, Xi’an, 710071, China 3 Information Technology Research Base of Civil Aviation Administration of China,

Civil Aviation University of China, Tianjin 300300, China

{jinxin,lxd}@besti.edu.cn

Abstract

    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.

Gallery

private-1

Parts of the foreground extraction results. The input plain video frames are shown in the first column. The extraction results in the server using our method are shown in the second column. The extraction results after the encryption and median filter in the client are shown in the third column. The extraction results in the server using the method in [2] are shown in the fourth column. The serve can clearly observe the contours of the foreground objects and the privacy of the client video is leaked. The ground truth manually segmented and annotated in [12] are shown in the last column. 

Paper and Slides

pdf
, , , , , , , , , :Private Video Foreground Extraction Through Chaotic Mapping Based Encryption in the Cloud. MMM (1) : 562-573.

video

slides

BibTeX

@inproceedings{DBLP:conf/mmm/JinGSLZLLCLW16,
  author    = {Xin Jin and
               Kui Guo and
               Chenggen Song and
               Xiaodong Li and
               Geng Zhao and
               Jing Luo and
               Yuzhen Li and
               Yingya Chen and
               Yan Liu and
               Huaichao Wang},
  title     = {Private Video Foreground Extraction Through Chaotic Mapping Based
               Encryption in the Cloud},
  booktitle = {MultiMedia Modeling - 22nd International Conference, {MMM} 2016, Miami,
               FL, USA, January 4-6, 2016, Proceedings, Part {I}},
  pages     = {562--573},
  year      = {2016},
  crossref  = {DBLP:conf/mmm/2016-1},
  url       = {https://doi.org/10.1007/978-3-319-27671-7_47},
  doi       = {10.1007/978-3-319-27671-7_47},
  timestamp = {Thu, 25 May 2017 00:40:52 +0200},
  biburl    = {http://dblp.uni-trier.de/rec/bib/conf/mmm/JinGSLZLLCLW16},
  bibsource = {dblp computer science bibliography, http://dblp.org}
}

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