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

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.

Authors

Publication Details

Journal
International Journal of Communication Networks and Distributed Systems
Published
2026-04-15
DOI
https://doi.org/10.1504/ijcnds.2027.10077735
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Amir Hosein Keyhanipour, Ahmad Farid Aseel
International Journal of Communication Networks and Distributed Systems
Network Security and Intrusion Detection
article

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

Amir Hosein Keyhanipour, Ahmad Farid Aseel
article en

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.

International Journal of Communication Networks and Distributed SystemsVol. 1(1)
Life in Land
Openalex Percentile: Top 5%
Network Security and Intrusion Detection
DOISourceOpenAlex
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Enhancing intrusion detection system performance under imbalanced data conditions using a hybrid deep learning framework — Amir Hosein Keyhanipour, Ahmad Farid Aseel · International Journal of Communication Networks and Distributed Systems (2026) | TGRS Research Map | TGRS