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Understanding trust in privacy-aware video surveillance systems

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Abstract

Recent advances in pervasive video surveillance systems pave the way for a comprehensive surveillance of every aspect of our lives, hence, leading us to a state of dataveillance. Computerized and interconnected systems of cameras could be used to profile, track and monitor individuals for the sake of security. Notwithstanding, these systems clearly interfere with the fundamental right of the individuals to privacy. Most literature on privacy in video surveillance systems concentrates on the goal of detecting faces and other regions of interest and in proposing different methods to protect them. However, the trustworthiness of those systems and, by extension, of the privacy they provide are mostly neglected. In this article, we define the concept of trustworthy privacy-aware video surveillance system. Moreover, we assess the techniques proposed in the literature according to their suitability for such a video surveillance system. Finally, we describe the properties that a deployment of a trustworthy video surveillance system must fulfill.

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Notes

  1. For the sake of completeness, we briefly introduce the concept of compressed video. A compressed video is a set of compressed frames, grouped in GOPs (Group of Pictures). Each GOP starts with an I-frame (intra-coded) and contains several P-frames (predicted) and B-frames (bi-predictive). I-frames are stored and compressed entirely: the frame is divided into blocks; a frequency transform (e.g., Discrete Cosine Transform) is applied to each block; a quantization is applied to each block (each frequency component is divided by a number, aiming at reducing the number of discrete symbols but resulting in a lossy compression and, also, a set of zero coefficients); finally, entropy encoding (for the nonzero coefficients) and run-length encoding (for the zero coefficients) are applied for a lossless compression of the block. The information needed to reconstruct the frame is stored in a specific and standardized data structure. In addition, P- and B-frames are not stored entirely: They just consist of the changing blocks between frames in the GOP.

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Acknowledgments

This work was partly funded by the Spanish Government through Project CONSOLIDER INGENIO 2010 CSD2007-0004 “ARES” and Project TIN2011-27076-C03-01 “CO-PRIVACY”, by the Government of Catalonia under Grant 2009 SGR 1135 and by Universitat Rovira i Virgili through Project 2012R2B-01 VIPP.

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Authors and Affiliations

  1. Dept. Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain

    Hatem A. Rashwan, Agusti Solanas, Domènec Puig & Antoni Martínez-Ballesté

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  1. Hatem A. Rashwan
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  2. Agusti Solanas
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  3. Domènec Puig
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Correspondence to Antoni Martínez-Ballesté.

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Rashwan, H.A., Solanas, A., Puig, D. et al. Understanding trust in privacy-aware video surveillance systems. Int. J. Inf. Secur. 15, 225–234 (2016). https://doi.org/10.1007/s10207-015-0286-9

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