Classification of Datasets Used in Data Anonymization for IoT Environment

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Classification of Datasets Used in Data Anonymization for IoT Environment

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Classification of Datasets Used in Data Anonymization for IoT Environment

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Advances and Trends in Artificial Intelligence :Theory and Applications

ISBN

978-981-9746-76-7

ISSN

0302-9743

e-ISSN

1611-3349

Počet stran výsledku

13

Strana od-do

80-92

Název nakladatele

Springer

Místo vydání

Singapore

Místo konání akce

Hradec Králové

Datum konání akce

10. 7. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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