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Electronics
Special Issues
Security in System and Software
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Security in System and Software

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (20 March 2025) | Viewed by 1005

Special Issue Editor

Dr. Wen Li

E-Mail Website
Guest Editor
Computer Science Department, Utah State University, Logan, UT 84322, USA
Interests: software security; software engineering; network security and privacy

Special Issue Information

Dear Colleagues,

The Special Issue on "Security in System and Software" delves into the multifaceted challenges and advancements in securing modern technological environments. It addresses the increasing complexity of cybersecurity in the face of emerging threats, particularly those posed by the rapid adoption of IoT, AI, and cloud technologies. This issue emphasizes the importance of integrating security into the software development lifecycle, offering insights into innovative security architectures and models. It also explores the latest tools and techniques for detecting vulnerabilities and conducting security assessments, including both automated and manual testing methods. Privacy and data protection are also key areas of focus, with discussions on how to implement privacy-preserving technologies and meet regulatory requirements like GDPR. In addition, this issue covers strategies for incident response and digital forensics, providing practical guidance on handling and investigating security breaches. Real-world case studies from various industries illustrate these concepts, highlighting the practical applications of research findings. Finally, the issue identifies current research gaps and suggests future directions, advocating for more interdisciplinary collaboration to tackle evolving security challenges.

Dr. Wen Li
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cybersecurity
  • system security
  • software vulnerabilities
  • secure development
  • privacy protection
  • incident response
  • digital forensics
  • security testing
  • emerging threats
  • interdisciplinary research

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

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Research

42 pages, 7989 KiB  
Article
Towards Robust SDN Security: A Comparative Analysis of Oversampling Techniques with ML and DL Classifiers
by Aboubakr Bajenaid, Maher Khemakhem, Fathy E. Eassa, Farid Bourennani, Junaid M. Qurashi, Abdulaziz A. Alsulami and Badraddin Alturki
Electronics 2025, 14(5), 995; https://doi.org/10.3390/electronics14050995 - 28 Feb 2025
Viewed by 645
Abstract
Software-defined networking (SDN) is becoming a predominant architecture for managing diverse networks. However, recent research has exhibited the susceptibility of SDN architectures to cyberattacks, which increases its security challenges. Many researchers have used machine learning (ML) and deep learning (DL) classifiers to mitigate [...] Read more.
Software-defined networking (SDN) is becoming a predominant architecture for managing diverse networks. However, recent research has exhibited the susceptibility of SDN architectures to cyberattacks, which increases its security challenges. Many researchers have used machine learning (ML) and deep learning (DL) classifiers to mitigate cyberattacks in SDN architectures. Since SDN datasets could suffer from class imbalance issues, the classification accuracy of predictive classifiers is undermined. Therefore, this research conducts a comparative analysis of the impact of utilizing oversampling and principal component analysis (PCA) techniques on ML and DL classifiers using publicly available SDN datasets. This approach combines mitigating the class imbalance issue and maintaining the effectiveness of the performance when reducing data dimensionality. Initially, the oversampling techniques are used to balance the classes of the SDN datasets. Then, the classification performance of ML and DL classifiers is evaluated and compared to observe the effectiveness of each oversampling technique on each classifier. PCA is applied to the balanced dataset, and the classifier’s performance is evaluated and compared. The results demonstrated that Random Oversampling outperformed the other balancing techniques. Furthermore, the XGBoost and Transformer classifiers were the most sensitive models when using oversampling and PCA algorithms. In addition, macro and weighted averages of evaluation metrics were calculated to show the impact of imbalanced class datasets on each classifier. Full article
(This article belongs to the Special Issue Security in System and Software)
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