What is the cost of privacy?

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F22%3AA2302FQL" target="_blank" >RIV/61988987:17310/22:A2302FQL - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-08974-9_55#citeas" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-08974-9_55#citeas</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-08974-9_55" target="_blank" >10.1007/978-3-031-08974-9_55</a>

Result language
angličtina
Original language name
What is the cost of privacy?
Original language description
Grade research has to be replicable, thus the used data need to be publicly available. Speaking, e.g., about object detection task, where image data for autonomous driving also contain privacy information such as faces and license plates, the publication of data may be harmful to captured people. The solution to the moral dilemma is to anonymize the data. In this study, our aim is to investigate the effect of various anonymization techniques on the performance of algorithms that use such data. We discuss anonymization methods that remove and replace privacy data and select three methods to replace the privacy data: blurring, permutation, and replacing the area with a constant value. We adopted the Cityscapes dataset from which we extracted areas containing privacy information and are the manner of the anonymization methods. Our benchmark involves three famous object detectors: YOLOv3, Mask R-CNN with ResNet-50 backbone, and Mask R-CNN with Swin-T backbone. The results show that the impact of anonymization methods on the performance is negligible and the impact is similar for both convolutional-based and transformer-based backbones.
Czech name
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Czech description
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Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Information Processing and Management of Uncertainty in Knowledge-Based Systems
ISBN
978-3-031-08974-9
ISSN
18650929
e-ISSN
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Number of pages
11
Pages from-to
696-706
Publisher name
Springer International Publishing
Place of publication
Cham
Event location
Milano
Event date
Jul 11, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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