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Towards a conceptual framework for AI-driven anomaly detection in smart city IoT networks for enhanced cybersecurity

Crossref DOI link: https://doi.org/10.1016/j.jik.2024.100601

Published Print: 2024-10

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Zeng, Heng

Yunis, Manal http://orcid.org/0000-0001-5545-7241
Khalil, Ayman http://orcid.org/0000-0002-5911-9642
Mirza, Nawazish
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Text and Data Mining valid from 2024-10-01

Text and Data Mining valid from 2024-10-01

Version of Record valid from 2024-10-15
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This article is maintained by: Elsevier

Article Title: Towards a conceptual framework for AI-driven anomaly detection in smart city IoT networks for enhanced cybersecurity

Journal Title: Journal of Innovation & Knowledge

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.jik.2024.100601

Content Type: article

Copyright: © 2024 The Authors. Published by Elsevier España, S.L.U. on behalf of Journal of Innovation & Knowledge.