Adversarial Machine Learning in Industrial IoT: A Systematic Review of Attack Realism, Defense Trade-Offs, and Deployment Gaps
- DOI
- 10.3390/s26165098
- Published
- 08
- Container
- Sensors
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
uncertain Score 53/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- supportingDirectory of Open Access Journals: A matching record was returned by DOAJ.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- supportingOpen access status: Normalized open-access status: open.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.3390/s26165098,
title = {Adversarial Machine Learning in Industrial IoT: A Systematic Review of Attack Realism, Defense Trade-Offs, and Deployment Gaps},
author = {Abeer Alsaidlani and Muhammad Rashid and Malak Aljabri},
year = {2026},
journal = {Sensors},
doi = {10.3390/s26165098},
url = {https://doi.org/10.3390/s26165098}
}RIS
TY - JOUR TI - Adversarial Machine Learning in Industrial IoT: A Systematic Review of Attack Realism, Defense Trade-Offs, and Deployment Gaps AU - Abeer Alsaidlani AU - Muhammad Rashid AU - Malak Aljabri PY - 2026 JO - Sensors DO - 10.3390/s26165098 UR - https://doi.org/10.3390/s26165098 ER -
APA
Alsaidlani, A., Rashid, M., & Aljabri, M. (2026). Adversarial Machine Learning in Industrial IoT: A Systematic Review of Attack Realism, Defense Trade-Offs, and Deployment Gaps. Sensors. https://doi.org/10.3390/s26165098
Source records
- doaj · retrieved 2026-09-25T00:32:35.885Z