TARU PUBLICATIONS
Journal of Information and Optimization Sciences cover
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis
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Open Access Research Article

Securing the future of wireless communications : Utilizing a blend of deep learning techniques for identifying risks in advanced communication networks

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* Corresponding author · click or hover a name for details

pp. 939–948Vol. 46Issue 4-AMay 2025DOI: 10.47974/JIOS-1819XML
Received:
11 Oct 2024
Published Online:
31 May 2025
Article type:
Research Article
Language:
EN
Article no.:
JIOS-1819
Pages:
939–948

Abstract

The rapid development of wireless communication and mobile networks, combined with broad use of IoT devices, has created substantial security concerns for core and edge networks. This study underlines the importance of installing strong security measures to combat new threats and encourages the creation of flexible security systems that may be tailored to future communication technologies. This research focuses on the boundaries of networks, where multiple nodes provide various services through terahertz radio frequency signals. This article presents a deep learning methodology that integrates convolutional neural network layers with LSTM for the analysis of sequential data. Using the NSL_KDD dataset as a comparison with conventional machine learning techniques, the new model shows better accuracy, detection rate, and fewer false alarms. This suggests its effectiveness in recognizing different types of attacks and minimizing incorrect identifications better accuracy, detection rate, and fewer false alarms. This suggests its effectiveness in recognizing different types of attacks and minimizing incorrect identifications.

Keywords

Subject Classifications

Primary 93A30Secondary 49K15

References

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