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Future Internet
Special Issues
Security of Computer System and Network
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Security of Computer System and Network

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Cybersecurity".

Deadline for manuscript submissions: 10 January 2026 | Viewed by 1107

Special Issue Editors

Dr. Pengfei Qiu

E-Mail Website
Guest Editor
Key Laboratory of Trustworthy Distributed Computing and Service, Beijing University of Posts and Telecommunications (BUPT), Ministry of Education, Beijing 100876, China
Interests: hardware security; hardware vulnerability mining; physical unclonable function; secure architecture design
Special Issues, Collections and Topics in MDPI journals
Dr. Eirini Eleni Tsiropoulou

E-Mail Website
Guest Editor
School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85281, USA
Interests: network modeling and optimization; IoT; cyber–physical systems; smart grid systems; network economics; wireless networks; social networks; cybersecurity; resource management; reinforcement learning; human behavior modeling; concentrated solar power systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Computer systems and networks are the foundation of modern society, and their security is critical to the security of the entire information system. However, vulnerabilities and attacks seriously threaten the security of data and finance, which also indicates that current computer systems and networks are not fully secure. In fact, the security of computer systems and networks has become a focus of recent research and attracted greater attention from researchers and industry.

Computer systems and networks are becoming increasingly complex and diverse; therefore, it is now urgent to detect the potential vulnerabilities of these networks and design security policies. This Special Issue focuses on innovative solutions to key challenges involving the vulnerability mining and defense strategies of computer systems and networks, and examines the application of novel technologies and methods in the field of computer security.

The scope of this Special Issue includes, but is not limited to, the following topics:

  1. Methods for vulnerability mining or security analysis.
  2. Fuzzing technologies for security analysis of computer system.
  3. Formal verification methods for security analysis of software.
  4. New vulnerabilities and their exploitation in computer systems and networks.
  5. The reverse-engineering and security analysis of block-box software.
  6. Security-enhanced strategies for computer systems and networks.
  7. Secure software architectures or frameworks.
  8. Secure software and network designs.
  9. Artificial intelligence-assisted security analysis and the design of countermeasures.

Dr. Pengfei Qiu
Dr. Eirini Eleni Tsiropoulou
Guest Editors

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. Future Internet is an international peer-reviewed open access monthly 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 1600 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

  • computer security
  • computer system security
  • network security
  • vulnerability mining
  • security analysis
  • software reverse-engineering
  • secure software
  • artificial intelligence-assisted security methods

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Published Papers (2 papers)

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25 pages, 1524 KiB  
Article
Detecting Emerging DGA Malware in Federated Environments via Variational Autoencoder-Based Clustering and Resource-Aware Client Selection
by Ma Viet Duc, Pham Minh Dang, Tran Thu Phuong, Truong Duc Truong, Vu Hai and Nguyen Huu Thanh
Future Internet 2025, 17(7), 299; https://doi.org/10.3390/fi17070299 - 3 Jul 2025
Viewed by 345
Abstract
Domain Generation Algorithms (DGAs) remain a persistent technique used by modern malware to establish stealthy command-and-control (C&C) channels, thereby evading traditional blacklist-based defenses. Detecting such evolving threats is especially challenging in decentralized environments where raw traffic data cannot be aggregated due to privacy [...] Read more.
Domain Generation Algorithms (DGAs) remain a persistent technique used by modern malware to establish stealthy command-and-control (C&C) channels, thereby evading traditional blacklist-based defenses. Detecting such evolving threats is especially challenging in decentralized environments where raw traffic data cannot be aggregated due to privacy or policy constraints. To address this, we present FedSAGE, a security-aware federated intrusion detection framework that combines Variational Autoencoder (VAE)-based latent representation learning with unsupervised clustering and resource-efficient client selection. Each client encodes its local domain traffic into a semantic latent space using a shared, pre-trained VAE trained solely on benign domains. These embeddings are clustered via affinity propagation to group clients with similar data distributions and identify outliers indicative of novel threats without requiring any labeled DGA samples. Within each cluster, FedSAGE selects only the fastest clients for training, balancing computational constraints with threat visibility. Experimental results from the multi-zones DGA dataset show that FedSAGE improves detection accuracy by up to 11.6% and reduces energy consumption by up to 93.8% compared to standard FedAvg under non-IID conditions. Notably, the latent clustering perfectly recovers ground-truth DGA family zones, enabling effective anomaly detection in a fully unsupervised manner while remaining privacy-preserving. These foundations demonstrate that FedSAGE is a practical and lightweight approach for decentralized detection of evasive malware, offering a viable solution for secure and adaptive defense in resource-constrained edge environments. Full article
(This article belongs to the Special Issue Security of Computer System and Network)
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Other

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36 pages, 2493 KiB  
Systematic Review
A Systematic Review of Cyber Range Taxonomies: Trends, Gaps, and a Proposed Taxonomy
by Pilleriin Lillemets, Nabaa Bashir Jawad, Joseph Kashi, Ahmad Sabah and Nicola Dragoni
Future Internet 2025, 17(6), 259; https://doi.org/10.3390/fi17060259 - 12 Jun 2025
Viewed by 560
Abstract
Cyber ranges have become essential platforms for realistic cybersecurity training, research, and development. Existing taxonomies often describe the functional aspects of cyber ranges—scenario design, team configurations, and evaluation metrics— focusing less on the underlying technologies that enable modern training. In this paper, we [...] Read more.
Cyber ranges have become essential platforms for realistic cybersecurity training, research, and development. Existing taxonomies often describe the functional aspects of cyber ranges—scenario design, team configurations, and evaluation metrics— focusing less on the underlying technologies that enable modern training. In this paper, we highlight the current trends and persistent gaps in the existing literature and propose a taxonomy that decouples functional capabilities from the enabling infrastructure, adding a dedicated Technology dimension. We derived and refined this taxonomy through an iterative literature mapping process, culminating in a proposed taxonomy that highlights key emerging trends such as cyber–physical integration, federation across multiple sites, and AI-driven orchestration. Key findings include the identification of clear convergences and divergences in existing taxonomies and concrete recommendations for future research directions, such as integrating socio-technical considerations and conducting systematic empirical validation. Our framework aims to guide researchers, developers, and practitioners in designing, implementing, and comparing cyber range solutions. An online Taxonomy Mapping Toolkit is developed to allow the cyber ranges research community to take advantage of the proposed taxonomy and build upon it as new advancements emerge. Full article
(This article belongs to the Special Issue Security of Computer System and Network)
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