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A Review on Machine Learning and Deep Learning Perspectives of IDS for IoT: Recent Updates, Security Issues, and Challenges

Thakkar, Ankit, Lohiya, Ritika·2021·Archives of Computational Methods in Engineering
DOI 10.1007/s11831-020-09496-0
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Cited by

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Metadata

Authors
Thakkar, A., & Lohiya, R.
Venue
Archives of Computational Methods in Engineering
Publisher
Springer Science and Business Media LLC
Published
2020-10-20
Volume
28
Issue
4
Pages
3211-3243
ISSN
  • 1134-3060 (ISSN-L)
  • 1886-1784
DOI
10.1007/s11831-020-09496-0
OpenAlex
W3093621053
Cited by
366
References
15
FWCI
18.62
Type
journal article
Language
en
Open access
closed
Licence

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This page
CoChat. (2026). Citation check: A Review on Machine Learning and Deep Learning Perspectives of IDS for IoT: Recent Updates, Security Issues, and Challenges. https://app.cochat.ai/papers/10.1007/s11831-020-09496-0
The paper
Thakkar, A., & Lohiya, R. (2021). A Review on Machine Learning and Deep Learning Perspectives of IDS for IoT: Recent Updates, Security Issues, and Challenges. Archives of Computational Methods in Engineering. https://doi.org/10.1007/s11831-020-09496-0

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.