Network Security and Network Protocols

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: 15 September 2025 | Viewed by 527

Special Issue Editors


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Guest Editor
School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China
Interests: reverse networks; network performance evaluation and management; network privacy enhancement and protection

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Guest Editor
Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China
Interests: anonymous communication; blockchain; privacy protection

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Guest Editor
Cyberspace Institute of Advanced Techology, Guangzhou University, Guangzhou 510006, China
Interests: edge computing; time-sensitive networks; industrial digital twins; LLM

Special Issue Information

Dear Colleagues,

In the digital era, where connectivity drives global progress, network protocols and network security form the foundation of modern communication systems. The scope and scale of networked environments have grown exponentially, as demonstrated by the rapid proliferation of devices, diversified networks, and emerging paradigms like the Satellite Internet,  Internet of Things (IoT), 5G/6G networks, edge computing, and quantum systems. This evolution has brought unparalleled advancements in connectivity and efficiency but simultaneously exposed networks to sophisticated security threats, privacy challenges, and vulnerabilities. Moreover, the Internet of today faces many novel challenges (e.g., AI-powered threats, quantum computing risks, and privacy erosion) that demand not only incremental improvements but also disruptive approaches to protocols and security frameworks.

This Special Issue on “Network Protocols and Network Security” provides a platform for researchers, industry experts, and practitioners to share cutting-edge solutions addressing these challenges. Specifically, it aims to advance the design, performance, and security of both foundational and emerging network protocols while catering to the growing need for secure, robust, and scalable solutions. Another major focus is addressing the growing demand for privacy-enhancing technologies, such as anonymous communication systems. In addition, the frequent cyberattacks occurring in the present day make the analysis of software and hardware vulnerabilities significantly more important. The thematic focus areas for this Special Issue include, but are not limited to:

  1. Security protocol design for Satellite Internet, 5G/6G, and IoT;
  2. Quantum networking protocols;
  3. Advanced intrusion detection and prevention systems (IDSs/IPSs);
  4. ML/AI/LLM-related threat detection, defense, and risk assessments;
  5. Anonymous communications and privacy-enhancing technologies;
  6. Blockchain-enabled security and decentralized identity management;
  7. Homomorphic encryption and differential privacy in federated learning;
  8. Software and hardware security vulnerability analysis;
  9. Cyber–physical system (CPS) security enhancement techniques.

Dr. Shengli Pan
Dr. Xuebin Wang
Dr. Chongwu Dong
Guest Editors

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Keywords

  • network protocol
  • Satellite Internet/IoT/5G/6G security
  • privacy-enhancing technologies
  • anonymous communication
  • quantum-safe communication
  • blockchain security
  • AI/LLM security
  • cyber–physical system security

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Published Papers (1 paper)

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Research

17 pages, 663 KiB  
Article
Session2vec: Session Modeling with Multi-Instance Learning for Accurate Malicious Web Robot Detection
by Jiachen Zhang, Shengli Pan, Daoqi Han, Zhanfeng Wang, Liangwei Yao and Yueming Lu
Electronics 2025, 14(10), 1945; https://doi.org/10.3390/electronics14101945 - 10 May 2025
Viewed by 320
Abstract
This study addresses the side effect of the rapid development of the Internet, positioning botnets within digital ecosystems as a very serious potential threat to the Internet users. Malicious web robot might facilitate Web/data scraping, DDoS attacks, and data theft yielding serious cybersecurity [...] Read more.
This study addresses the side effect of the rapid development of the Internet, positioning botnets within digital ecosystems as a very serious potential threat to the Internet users. Malicious web robot might facilitate Web/data scraping, DDoS attacks, and data theft yielding serious cybersecurity threats. Modern botnets are advanced and have unique browser fingerprints, making their detection a real challenge. Traditional feature extraction methods heavily depend on expert knowledge. They also struggle with dimensional inconsistency when processing sessions of varying lengths, failing to counter evolving camouflage attacks. To approach such challenges, we propose Session2vec, a session representation framework based on multi-instance learning (MIL), which pioneers the MIL approach for Web session modeling. In this approach, we treat each request as an instance and the entire session as an instance collection, and then we use the FastText model to convert each URL request into a vector representation. Then, we utilize two innovative multi-instance aggregation methods: SARD (Session-level Aggregated Residual Descriptors) and SFAR (Session-level Fisher Aggregated Representation) to aggregate variable-length sessions into fixed-dimensional vectors capturing spatiotemporal features and distributional information within sessions. Simulation results of the proposed SARD and SFAR methods on public datasets show accuracy improvement of 5.2% and 16.3% on average, respectively, compared to state-of-the-art baselines. They also enhance F1 scores by 8.5% and 19.7%, respectively. Full article
(This article belongs to the Special Issue Network Security and Network Protocols)
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