PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 6, 2026Open Access

Arabic Natural Language Processing for Cybersecurity Applications: A Deep Learning Approach to Threat Detection in Arabic Content

View Full Paper
Ask AI
Bookmark
Share

Authors

SMSafa MohamedSKSafa Kamal

Discussion

Loading...

Member takes

Overview

Deep learning methods improve threat detection accuracy in Arabic content, suggesting better cybersecurity applications.

Key Points

  • The research aims to enhance cybersecurity through effective Arabic natural language processing techniques.
  • Developed a deep learning approach for threat detection in Arabic content.
  • Evaluated convolutional and recurrent neural networks for Arabic cybersecurity classification tasks.
  • Integrated Arabic-specific preprocessing and contextual word embeddings.
  • Conducted experiments on a curated dataset of Arabic cybersecurity content.
  • Achieved 93.4% accuracy in threat detection with transformer-based architecture.
  • Outperformed traditional machine learning baselines by 18.7 percentage points.
  • Guided by comparative analysis of Arabic text representation strategies.

Cite This Study

Mohamed et al. (2025) studied this question.

synapsesocial.com/papers/69fa8eac04f884e66b531029https://doi.org/10.5281/zenodo.20023264
View Full Paper
Ask AI
Bookmark
Share