Title: Leveraging advanced deep learning algorithms to combat fake news in Arabic media landscape

Authors: K. Chitra; E. Srimathi; R. Rajpriya; Edwin Shalom Soji; R. Balamurugan; S. Silvia Priscila

Addresses: Department of Master of Computer Applications, Dayananda Sagar Academy of Technology and Management, Bangalore, Karnataka, India ' Department of Computer Applications, SRM Institute of Science and Technology, Ramapuram Campus, Chennai, Tamil Nadu, India ' Department of Computer Applications, Chennai National Arts and Science College, Avadi, Chennai, Tamil Nadu, India ' Department of Computer Science, Bharath Institute of Higher Education and Research, Chennai, Tamil Nadu, India ' Department of Information Technology, DMI College of Engineering, Chennai, Tamil Nadu, India ' Department of Computer Science, Bharath Institute of Higher Education and Research, Chennai, Tamil Nadu, India

Abstract: The increasing presence of false information online in today's digital era can lead to societal issues such as political upheavals and the circulation of incorrect data. This study introduces a unique method to identify untrue reports in Arabic utilising advanced deep learning methods. We review existing literature on fake news detection and discuss the challenges specific to Arabic language processing. Our approach entails creating a deep learning architecture customised to Arabic language and extensively evaluating its performance. Results, graphical representations, tables, mathematical equations, and model efficacy discussions are presented. While our approach shows promising results, we also acknowledge its limitations and propose future research directions. However, the journey continues. Research and innovation are needed to address dataset scarcity, model interpretability, and adversarial attacks. Staying ahead of disinformation providers' increasingly sophisticated strategies is crucial as the digital world advances. This study guides us and reminds us of the challenges ahead. With this research's tools and insights, we can fight fake news better.

Keywords: false information identification; advanced learning methods; Arabic tongue; linguistic data processing; neural systems; text classification; sentiment analysis; information warfare.

DOI: 10.1504/IJESDF.2026.153331

International Journal of Electronic Security and Digital Forensics, 2026 Vol.18 No.3, pp.348 - 369

Received: 28 Mar 2024
Accepted: 29 Jul 2024
Published online: 01 May 2026 *

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