Classification of Datasets Used in Data Anonymization for IoT Environment
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F24%3A50021808" target="_blank" >RIV/62690094:18450/24:50021808 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/10.1007/978-981-97-4677-4_8" target="_blank" >https://link.springer.com/10.1007/978-981-97-4677-4_8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-981-97-4677-4_8" target="_blank" >10.1007/978-981-97-4677-4_8</a>
Alternative languages
Result language
angličtina
Original language name
Classification of Datasets Used in Data Anonymization for IoT Environment
Original language description
The integration of Internet of Things (IoT) devices in smart cities facilitates the collection, sharing, and analysis of data to optimize city services, enhance residents’ well-being, and enable more efficient decision-making processes. Balancing the benefits of IoT data collection and sharing with the imperative of preserving user privacy involves implementing robust security measures and anonymization techniques to ensure the safety, security, and trustworthiness of IoT technologies. Anonymization techniques enable service providers to collect, store, and share data while preserving user privacy, with various methods applicable across different types. This paper presents a literature review focusing on data anonymization in the IoT environment, aiming to classify datasets used to evaluate newly proposed anonymization methods, examining their types, availability, size, and applicability in research. The study aims to provide insights into the datasets employed in data anonymization research for IoT environments and determine the level of using relational datasets in such studies.
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
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances and Trends in Artificial Intelligence :Theory and Applications
ISBN
978-981-9746-76-7
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
13
Pages from-to
80-92
Publisher name
Springer
Place of publication
Singapore
Event location
Hradec Králové
Event date
Jul 10, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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