Retraction Note: An optimized Bi-LSTM with random synthetic over-sampling strategy for network intrusion detection.

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Bibliographic Details
Title: Retraction Note: An optimized Bi-LSTM with random synthetic over-sampling strategy for network intrusion detection.
Authors: Padmavathi, B.1 (AUTHOR), Bhagyalakshmi, A.1 (AUTHOR), Kavitha, D.1 (AUTHOR), Indumathy, P.1 (AUTHOR) csrdpadma@gmail.com
Source: Soft Computing - A Fusion of Foundations, Methodologies & Applications. 2026 Suppl 1, Vol. 30, p541-541. 1p.
Subjects: Retraction of scholarly articles, Editorial policies, Professional peer review, Intrusion detection systems (Computer security), Long short-term memory
Abstract: This retraction notice addresses the withdrawal of a previously published article due to concerns identified in an investigation by the publisher. The issues include compromised editorial handling and peer review processes, inappropriate or irrelevant references, and the article being outside the journal's scope. As a result, the publisher and Editor-in-Chief have lost confidence in the article's results and conclusions. The authors did not respond to correspondence regarding the retraction. [Extracted from the article]
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Database: Engineering Source
Description
Abstract:This retraction notice addresses the withdrawal of a previously published article due to concerns identified in an investigation by the publisher. The issues include compromised editorial handling and peer review processes, inappropriate or irrelevant references, and the article being outside the journal's scope. As a result, the publisher and Editor-in-Chief have lost confidence in the article's results and conclusions. The authors did not respond to correspondence regarding the retraction. [Extracted from the article]
ISSN:14327643
DOI:10.1007/s00500-025-11090-0