Artificial intelligence control for trust‐based detection of attackers in 5G social networks
Artificial intelligence control for trust‐based detection of attackers in 5G social networks
About this item
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Author / Creator
Publisher
Hoboken: Blackwell Publishing Ltd
Journal title
Language
English
Formats
Publication information
Publisher
Hoboken: Blackwell Publishing Ltd
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Scope and Contents
Contents
This study introduces a comprehensive framework designed for detecting and mitigating fake and potentially threatening user communities within 5G social networks. Leveraging geo‐location data, community trust dynamics, and AI‐driven community detection algorithms, this framework aims to pinpoint users posing potential harm. Including an artificial...
Alternative Titles
Full title
Artificial intelligence control for trust‐based detection of attackers in 5G social networks
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2930966834
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2930966834
Other Identifiers
ISSN
0824-7935
E-ISSN
1467-8640
DOI
10.1111/coin.12618
