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September 5, 2025Scholarly review .

Comparing Machine Learning Algorithms for Intrusion Detection Systems

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Authors

LLLawrence Liu

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Overview

Experiments demonstrate that Random Forest outperforms deep learning models for IDS accuracy, highlighting challenges in complex cyber threats.

Key Points

  • Random Forest outperforms deep learning models in intrusion detection accuracy and processing time.
  • Significant variations in model performance were observed across different datasets, particularly UNSW-NB15.
  • The study utilized several machine learning techniques to assess a wide range of cyber attack types.
  • Further advancements in IDS models are necessary to effectively combat evolving cyber threats.

Cite This Study

Lawrence Liu (2025) studied this question.

synapsesocial.com/papers/68bb4e016d6d5674bcd02a4ehttps://doi.org/10.70121/001c.143877
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A Systematic Analysis and Review on Intrusion Detection Systems Using Machine Learning and Deep Learning Algorithms2024 · 2 citations
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  4. 4Evaluating Security enhancement through Machine Learning Approaches for Anomaly Based Intrusion Detection Systems2024 · 3 citations
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