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Title: Privacy modeling for video data publication
Authors: Saini, M.
Atrey, P.K.
Mehrotra, S.
Emmanuel, S.
Kankanhalli, M. 
Keywords: Identity leakage
Video surveillance
Issue Date: 2010
Citation: 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.
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
ISBN: 9781424474912
DOI: 10.1109/ICME.2010.5583334
Appears in Collections:Staff Publications

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