Sentinel: Signal Validation and Anomaly Detection for Enterprise Log Data

Jupyter Notebook Python Submitted 27 March 2026 • Published 07 November 2026
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Editor: @nkrusch (all papers)
Reviewers: @kishanraj41 (all reviews), @khushboo2243 (all reviews)

Authors

José Manuel Vergara Álvarez (0000-0002-5401-5342), Nicolás Laverde Manotas (0009-0002-3578-694X), Juan Pablo Aguilar Calle (0009-0001-9109-393X), Jeisson Vicente Niño Castillo (0009-0009-2320-8246), Julián David Muñoz Pertuz (0009-0006-0076-1696), Daniel Monsalve Muñoz (0009-0003-4775-2058), Sebastián Osorio Agudelo (0009-0004-9903-1807)

Citation

Álvarez et al., (2026). Sentinel: Signal Validation and Anomaly Detection for Enterprise Log Data. Journal of Open Source Software, 11(127), 11275, https://doi.org/10.21105/joss.11275

@article{Álvarez2026, doi = {10.21105/joss.11275}, url = {https://doi.org/10.21105/joss.11275}, year = {2026}, publisher = {The Open Journal}, volume = {11}, number = {127}, pages = {11275}, author = {Álvarez, José Manuel Vergara and Manotas, Nicolás Laverde and Calle, Juan Pablo Aguilar and Castillo, Jeisson Vicente Niño and Pertuz, Julián David Muñoz and Muñoz, Daniel Monsalve and Agudelo, Sebastián Osorio}, title = {Sentinel: Signal Validation and Anomaly Detection for Enterprise Log Data}, journal = {Journal of Open Source Software} }
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log analysis anomaly detection signal validation enterprise logs

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Authors of JOSS papers retain copyright.

This work is licensed under a Creative Commons Attribution 4.0 International License.

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Journal of Open Source Software is an affiliate of the Open Source Initiative.

Journal of Open Source Software is part of Open Journals, which is a NumFOCUS-sponsored project.

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ISSN 2475-9066