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April 17, 2026International Journal of Communication Networks and Distributed Systems0 citations

Enhancing intrusion detection system performance under imbalanced data conditions using a hybrid deep learning framework

AAAhmad Farid AseelAKAmir Hosein Keyhanipour

Key Points

  • To improve the performance of intrusion detection systems when facing imbalanced data.
  • Developed a hybrid deep learning framework for intrusion detection.
  • Analyzed the performance under varying conditions of data imbalance.
  • Implemented various techniques to enhance detection rates.
  • Achieved higher accuracy in detecting intrusions compared to traditional methods.
  • Demonstrated improved detection rates for minority classes in imbalanced datasets.

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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Cite This Study

Aseel et al. (2026) studied this question.

synapsesocial.com/papers/69e1cefb5cdc762e9d857f6fhttps://doi.org/10.1504/ijcnds.2027.10077735
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Also Consider

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

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