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Applied Sciences
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Radio Relay Networks and Microwave Techniques: Advances and Applications
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Radio Relay Networks and Microwave Techniques: Advances and Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: 20 February 2025 | Viewed by 2495

Special Issue Editors

Dr. Grigor Mihaylov

E-Mail Website
Guest Editor
Department of Telecommunications, University of Telecommunications and Post, 1700 Sofia, Bulgaria
Interests: digital communications; wireless communications; mobile networks
Dr. Ivaylo Stoyanov

E-Mail Website
Guest Editor
Department of Power Engineering, University of Ruse, 7004 Ruse, Bulgaria
Interests: renewable energy sources; electromagnetic compatibility; electrotechnical safety; smart grid; electric power transmission
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As mobile network capacity demands have increased rapidly, a large number of the operator's investments are directed towards the deployment of ultra-wide-band communications. Millimeter wave (mmW) facilitates the transmission of many subcarriers, offering the following advantages: huge bandwidth, narrow beam, high-quality transmission, etc. The rapid emergence of 5G networks has set a number of new planning problems which should be carefully analyzed to optimize the installation of new technologies and integrate them in the existing mobile network. Energy and cost efficiency are becoming increasingly important criteria in the design of 5G radio relay lines, especially for areas close to water surfaces, where there is pronounced fading, characteristic of radio relay paths that pass on the surface of the water.

Dr. Grigor Mihaylov
Dr. Ivaylo Stoyanov
Guest Editors

Manuscript Submission Information

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Keywords

  • radio relay networks
  • MIMO systems
  • radio access networks
  • network topology
  • line-of-sight
  • network planning
  • fading
  • 5G technology

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Published Papers (1 paper)

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Research

26 pages, 5102 KiB  
Article
A Novel Feature Selection Approach to Classify Intrusion Attacks in Network Communications
by Merve Ozkan-Okay, Refik Samet, Ömer Aslan, Selahattin Kosunalp, Teodor Iliev and Ivaylo Stoyanov
Appl. Sci. 2023, 13(19), 11067; https://doi.org/10.3390/app131911067 - 8 Oct 2023
Cited by 7 | Viewed by 2006
Abstract
The fast development of communication technologies and computer systems brings several challenges from a security point of view. The increasing number of IoT devices as well as other computing devices make network communications more challenging. The number, sophistication, and severity of network-related attacks [...] Read more.
The fast development of communication technologies and computer systems brings several challenges from a security point of view. The increasing number of IoT devices as well as other computing devices make network communications more challenging. The number, sophistication, and severity of network-related attacks are growing rapidly. There are a variety of different attacks including remote-to-user (R2L), user-to-remote (U2R), denial of service (DoS), distributed DDoS, and probing. Firewalls, antivirus scanners, intrusion detection systems (IDSs), and intrusion prevention systems (IPSs) are widely used to prevent and stop cyber-related attacks. Especially, IDPSs are used to stop and prevent intrusions on communication networks. However, traditional IDSs are no longer effective in detecting complicated cyber attacks from normal network traffic. Because of this, new promising techniques, which specifically utilize data mining, machine learning, and deep learning, need to be proposed in order to distinguish intrusions from normal network traffic. To effectively recognize intrusions, the feature generation, feature selection, and learning processes must be performed delicately before the classification stage. In this study, a new feature selection method called FSAP (Feature Selection Approach) is proposed. In addition, a hybrid attack detection model called SABADT (Signature- and Anomaly-Based Attack Detection Technique) is suggested, which utilizes different classification metrics to recognize attacks. The proposed general method FSACM (Feature Selection and Attack Classification Method) is tested on KDD ’99, UNSW-NB15, and CIC-IDS2017 datasets. According to the experiment results, the proposed method outperformed the state-of-the-art methods in the literature in terms of detection, accuracy, and false-alarm rates. Full article
(This article belongs to the Special Issue Radio Relay Networks and Microwave Techniques: Advances and Applications)
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