Expression of Concern : PRIFLEX: A Secure Federated Learning Framework for Evaluating Privacy Leakage and Defense in Cross-Modal Medical Data

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Abstract

EXPRESSION OF CONCERN FOR: Mohammad Othman Nassar, Feras Fares AL-Mashagba. (2025). PRIFLEX: A Secure Federated Learning Framework for Evaluating Privacy Leakage and Defense in Cross-Modal Medical


Data. Mesopotamian Journal of CyberSecurity, 5(1), 1057-1080.


https://doi.org/10.58496/MJCS/2025/057


https://journals.mesopotamian.press/index.php/CyberSecurity/article/view/922


Reason for Expression of Concern:


The Editors wish to alert readers to potential concerns regarding the reliability of the findings reported in “PRIFLEX: A Secure Federated Learning Framework for Evaluating Privacy Leakage and Defense in Cross-Modal Medical Data”. The journal has initiated an additional editorial assessment of the article’s methodology, data provenance, and reported outcomes to confirm their reliability and reproducibility.


This notice is issued to ensure transparency while the review is ongoing. The Expression of Concern does not constitute a final determination regarding the validity of the work. The journal will update readers once the assessment is completed and will take any necessary editorial action in accordance with the journal’s policies and COPE guidance.

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How to Cite

Expression of Concern : PRIFLEX: A Secure Federated Learning Framework for Evaluating Privacy Leakage and Defense in Cross-Modal Medical Data. (2026). Mesopotamian Journal of CyberSecurity, 2026(1), 16-16. https://doi.org/10.58496/2026/016

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