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Abstract

In the age of digital media, securing personal identities in shared material, especially on social media, has become a significant challenge. This research leverages software engineering to automate face blurring in photographs of Arab social media personalities. It proposes a system that integrates sophisticated deep-learning algorithms with standard image processing within a robust software architecture. This modular system is scalable, maintainable, and compatible with digital media platforms. Gaussian blur is applied to protect privacy once convolutional neural networks (CNNs) identify faces. The system’s efficiency and accuracy are enhanced by OpenCV and NumPy. In experiments, this system consistently identifies and blurs faces with over 90% accuracy, making it a reliable tool for digital media privacy. The system’s modularity and flexibility enable its easy integration and modification across applications, in adherence to software engineering principles such as reusability, scalability, and maintainability.

Reason for Expression of Concern:The Editors wish to alert readers to potential concerns regarding the reliability of the findings reported in ``Software Engineering Approach to Enhancing Privacy Protection: Automated Face Blurring Using Deep Learning in Arab Social Media (Manuscript 1317)''. 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." See expression of concern available at:
DOI: https://doi.org/10.52866/2788-7421.1388.
Available at: http://ijcsm.researchcommons.org/ijcsm/vol7/iss1/42

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