Publishing video data with indistinguishable objects

Han Wang, Yuan Hong, Yu Kong, Jaideep Vaidya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


Millions of videos are ubiquitously generated and shared everyday. Releasing videos would be greatly beneficial to social interactions and the community but may result in severe privacy concerns. To the best of our knowledge, most of the existing privacy preserving techniques for video data focus on detecting and blurring the sensitive regions in the video. Such simple privacy models have two major limitations: (1) they cannot quantify and bound the privacy risks, and (2) they cannot address the inferences drawn from the background knowledge on the involved objects in the videos. In this paper, we first define a novel privacy notion ϵ-Object Indistinguishability for all the predefined sensitive objects (e.g., humans and vehicles) in the video, and then propose a video sanitization technique VERRO that randomly generates utility-driven synthetic videos with indistinguishable objects. Therefore, all the objects can be well protected in the generated utility-driven synthetic videos which can be disclosed to any untrusted video recipient. We have conducted extensive experiments on three real videos captured for pedestrians on the streets. The experimental results demonstrate that the generated synthetic videos lie close to the original video for retaining good utility while ensuring rigorous privacy guarantee.

Original languageEnglish (US)
Title of host publicationAdvances in Database Technology - EDBT 2020
Subtitle of host publication23rd International Conference on Extending Database Technology, Proceedings
EditorsAngela Bonifati, Yongluan Zhou, Marcos Antonio Vaz Salles, Alexander Bohm, Dan Olteanu, George Fletcher, Arijit Khan, Bin Yang
Number of pages12
ISBN (Electronic)9783893180837
StatePublished - 2020
Event23rd International Conference on Extending Database Technology, EDBT 2020 - Copenhagen, Denmark
Duration: Mar 30 2020Apr 2 2020

Publication series

NameAdvances in Database Technology - EDBT
ISSN (Electronic)2367-2005


Conference23rd International Conference on Extending Database Technology, EDBT 2020

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Software
  • Computer Science Applications


Dive into the research topics of 'Publishing video data with indistinguishable objects'. Together they form a unique fingerprint.

Cite this