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September 27, 2025Open Access

Integrating Machine Learning and Artificial Intelligence for Next-Generation Cybersecurity in Computer Science Applications

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Authors

NANaveed Akhtar

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Overview

A hybrid deep learning framework improves intrusion detection accuracy in cybersecurity, suggesting potential for future real-time applications.

Key Points

  • CS-MLAI-Net achieved a detection accuracy of 98.7%, significantly outperforming traditional cybersecurity methods.
  • The framework combines CNNs and BiLSTM architectures for effective feature extraction and attack pattern recognition.
  • Comprehensive evaluations on NSL-KDD and CICIDS-2017 datasets showcased robustness against diverse intrusion types.
  • This research highlights the transformative potential of AI-driven approaches in enhancing digital infrastructure security.

Cite This Study

Naveed Akhtar (2025) studied this question.

synapsesocial.com/papers/68d7be5eeebfec0fc52375b6https://doi.org/10.21203/rs.3.rs-7703315/v1
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