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Erschienen in:
Towards Efficient Evaluation of a Time-Driven Cache Attack on Modern Processors Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

A Formal Treatment of Privacy in Video Data

verfasst von : Valerie Fetzer, Jörn Müller-Quade, Tobias Nilges

Erschienen in: Computer Security – ESORICS 2016

Verlag: Springer International Publishing

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Abstract

Video surveillance has become prevalent both in public spaces, e.g. to prevent crimes, and in private areas, e.g. in order to assist the staff in assisted living communities. This leads to privacy concerns regarding the ability of third parties to create profiles and track individuals, possibly across several services.
Usually, techniques such as pixelation and silhouettes are used to anonymize individuals. However, no formal treatment of privacy for video data has been proposed and current anonymization techniques are simply “best practice”. To resolve this unsatisfactory state of affairs, we initiate a formal treatment of privacy in video data and propose a game-based notion for privacy in video data that is inspired by cryptographic security games.
We show for an exemplary video privacy scheme that this scheme satisfies our notion with good parameters. In order to evaluate these parameters, we conduct a user study where the users essentially play the role of the adversary in the privacy game. Our approach can be used as a blueprint to evaluate the privacy of other video privacy schemes.

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Vorheriges Kapitel Quantifying Location Privacy Leakage from Transaction Prices
Nächstes Kapitel On Attacker Models and Profiles for Cyber-Physical Systems
Fußnoten
1
We focus on hiding information about individuals in video data. This does not directly translate into anonymity. Instead, it limits the number of features that are available to identify individuals, which in turn can lead to (some form of) anonymity, depending on the scenario.
 
2
Please note that we only had a limited dataset available. In real scenarios, the operators of surveillance systems should be able to obtain a larger dataset and more representative results.
 
3
One might argue that it is very difficult to explicitly state all features that are not hidden, but we show in Sect. 4.4 that a good approximation seems to be sufficient in most cases.
 
4
Our discussion in Sect. 4.5 elaborates on the problems that arise when cutting the videos.
 
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Metadaten
Titel
A Formal Treatment of Privacy in Video Data
verfasst von
Valerie Fetzer
Jörn Müller-Quade
Tobias Nilges
Copyright-Jahr
2016
Buch
Computer Security – ESORICS 2016

Print ISBN: 978-3-319-45740-6

Electronic ISBN: 978-3-319-45741-3

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-45741-3_21

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