Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICME.2010.5583334
Title: Privacy modeling for video data publication
Authors: Saini, M.
Atrey, P.K.
Mehrotra, S.
Emmanuel, S.
Kankanhalli, M. 
Keywords: Identity leakage
Privacy
Video surveillance
Issue Date: 2010
Source: Saini, M., Atrey, P.K., Mehrotra, S., Emmanuel, S., Kankanhalli, M. (2010). Privacy modeling for video data publication. 2010 IEEE International Conference on Multimedia and Expo, ICME 2010 : 60-65. ScholarBank@NUS Repository. https://doi.org/10.1109/ICME.2010.5583334
Abstract: Video cameras are being extensively used in many applications. Huge amounts of video are being recorded and stored everyday by surveillance systems. Any proposed application of this data raises severe privacy concerns. An assessment of privacy loss is necessary before any potential application of the data. In traditional methods of privacy modeling, researchers have focused on explicit means of identity leakage like facial information, etc. However, other implicit inference channels through which individual's an identity can be learned have not been considered. For example, an adversary can observe the behavior, look at the places visited and combine that with the temporal information to infer the identity of the person in the video. In this work, we thoroughly investigate privacy issues involved with the video data considering both implicit and explicit channels. We first establish an analogy with the statistical databases and then propose a model to calculate the privacy loss that might occur due to publication of the video data. The experimental results demonstrate the utility of the proposed model. © 2010 IEEE.
Source Title: 2010 IEEE International Conference on Multimedia and Expo, ICME 2010
URI: http://scholarbank.nus.edu.sg/handle/10635/40173
ISBN: 9781424474912
DOI: 10.1109/ICME.2010.5583334
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

16
checked on Dec 6, 2017

WEB OF SCIENCETM
Citations

9
checked on Nov 20, 2017

Page view(s)

52
checked on Dec 10, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.