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Deep learning-enabled anomaly detection for IoT systems

Adel Abusitta, Glaucio H. S. de Carvalho, Omar Abdul Wahab, Talal Halabi, Benjamin C. M. Fung and Saja Al Mamoori

Article (2023)

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Department: Department of Computer Engineering and Software Engineering
PolyPublie URL: https://publications.polymtl.ca/52206/
Journal Title: Internet of Things (vol. 21)
Publisher: Elsevier
DOI: 10.1016/j.iot.2022.100656
Official URL: https://doi.org/10.1016/j.iot.2022.100656
Date Deposited: 18 Apr 2023 14:58
Last Modified: 05 Apr 2024 11:57
Cite in APA 7: Abusitta, A., de Carvalho, G. H. S., Abdul Wahab, O., Halabi, T., Fung, B. C. M., & Al Mamoori, S. (2023). Deep learning-enabled anomaly detection for IoT systems. Internet of Things, 21, 100656 (13 pages). https://doi.org/10.1016/j.iot.2022.100656

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