The impact of anonymization on the geosocial network metrics used in socio-economic analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F20%3A50016714" target="_blank" >RIV/62690094:18450/20:50016714 - isvavai.cz</a>
Result on the web
<a href="http://doi.org/10.36689/uhk/hed/2020-01-062" target="_blank" >http://doi.org/10.36689/uhk/hed/2020-01-062</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.36689/uhk/hed/2020-01-062" target="_blank" >10.36689/uhk/hed/2020-01-062</a>
Alternative languages
Result language
angličtina
Original language name
The impact of anonymization on the geosocial network metrics used in socio-economic analysis
Original language description
The expansion of mobile devices equipped with GPS (Global Positioning System) locators corresponds to the development of the highly customized location-based services including geosocial networks. The usage of customized location-based services positively effects many aspects of users’ daily routines from travelling to choosing the best restaurant. On the other hand, providing customized services relates to collecting and storing large amount of users’ information and gives rise to many privacy-preserving issues. In this paper, we discuss the privacy concerns connected with publishing geosocial network datasets and the impact of the anonymization on the utility of the geosocial network dataset. Considering the importance of the geosocial network for the socioeconomic analysis, we put arguments for the importance of geosocial network anonymization before exploiting the dataset. We apply the clustering anonymization methods according to geographical coordinates and the values of location entropy on the real-world data to prevent the location privacy leakage. Afterwards, we compare the network metrics in the original and anonymized real-world datasets and measure the impact of the anonymization on the metric values.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the international scientific conference Hradec Economic Days 2020
ISBN
978-80-7435-776-3
ISSN
2464-6059
e-ISSN
2464-6067
Number of pages
8
Pages from-to
543-550
Publisher name
Univerzita Hradec Králové
Place of publication
Hradec Králové
Event location
Hradec Králové
Event date
Apr 2, 2020
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
000568108700060