AI-driven cybersecurity framework for anomaly detection in power systems

Vignes V. M., Sri Harini M. P., Rahul Satheesh, Vipin Das, Sanjeevikumar Padmanaban

Open source

DOI: 10.1038/s41598-025-19634-y
Published: 2025-10-10
Container: Scientific Reports
Publisher: Springer Science and Business Media LLC
Open access: unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

supportingDOI registered: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
supportingDOI resolves: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1038/s41598-025-19634-y,
  title = {AI-driven cybersecurity framework for anomaly detection in power systems},
  author = {Vignes V. M. and Sri Harini M. P. and Rahul Satheesh and Vipin Das and Sanjeevikumar Padmanaban},
  year = {2025},
  journal = {Scientific Reports},
  doi = {10.1038/s41598-025-19634-y},
  url = {https://doi.org/10.1038/s41598-025-19634-y}
}

RIS

TY  - JOUR
TI  - AI-driven cybersecurity framework for anomaly detection in power systems
AU  - Vignes V. M.
AU  - Sri Harini M. P.
AU  - Rahul Satheesh
AU  - Vipin Das
AU  - Sanjeevikumar Padmanaban
PY  - 2025
JO  - Scientific Reports
DO  - 10.1038/s41598-025-19634-y
UR  - https://doi.org/10.1038/s41598-025-19634-y
ER  -

APA

M., V. V., P., S. H. M., Satheesh, R., Das, V., & Padmanaban, S. (2025). AI-driven cybersecurity framework for anomaly detection in power systems. Scientific Reports. https://doi.org/10.1038/s41598-025-19634-y

Source records

crossref · retrieved 2026-09-26T05:29:25.250Z