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Mathematics
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Research and Application of Network and System Security
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Research and Application of Network and System Security

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".

Deadline for manuscript submissions: 31 March 2026 | Viewed by 464

Special Issue Editors

Dr. Donghai Tian

E-Mail Website
Guest Editor
Beijing Key Laboratory of Software Security Engineering Technique, Beijing Institute of Technology, Beijing 100081, China
Interests: software security; malware analysis and detection; Android system security; big data security; cloud computing
Dr. Ping Chen

E-Mail Website
Guest Editor
Institute of BigData, Fudan University, Shanghai, China
Interests: software and system security

Special Issue Information

Dear Colleagues,

We are pleased to announce this Special Issue of the Mathematics journal, entitled "Research and Application of Network and System Security". In today's interconnected world, the emergence of Intelligent Connected Vehicles, Industrial Control Systems, and Cloud–Edge Collaboration Architecture has significantly expanded attack surfaces. Cybersecurity threats are becoming more complex and cross-domain in nature, demanding sophisticated defense strategies. We invite the submission of cutting-edge research on Dynamic Heterogeneous Redundancy models that enhance system resilience against Cross-Domain Attacks. Contributions addressing Game theory-based Attack Evaluation frameworks for dynamic threat assessment are highly encouraged. We also welcome studies exploring how AI can optimize Integrated Safety Protection mechanisms in multi-layered architectures. In this evolving landscape, cyber mimic defense, leveraging behavioral mimicry to detect and counteract sophisticated threats, has emerged as a critical component of Dynamic Defense strategies. Research on how Cloud Computing and Edge Computing can support real-time threat detection and response in these systems will be particularly valuable to advancing the field of cybersecurity.

Dr. Donghai Tian
Dr. Ping Chen
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. Mathematics 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 2600 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

  • dynamic heterogeneous redundancy
  • computational intelligence
  • network security
  • mathematical cryptography
  • cybersecurity
  • malware analysis
  • threat prediction
  • algebraic structures
  • neural networks
  • optimization algorithms
  • computational complexity
  • mimic defense
  • cloud computing
  • edge computing
  • intelligent connected vehicles

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

Published Papers (2 papers)

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Research

17 pages, 1419 KiB  
Article
Research on Endogenous Security Defense for Cloud-Edge Collaborative Industrial Control Systems Based on Luenberger Observer
by Lin Guan, Ci Tao and Ping Chen
Mathematics 2025, 13(17), 2703; https://doi.org/10.3390/math13172703 - 22 Aug 2025
Abstract
Industrial Control Systems (ICSs) are fundamental to critical infrastructure, yet they face increasing cybersecurity threats, particularly data integrity attacks like replay and data forgery attacks. Traditional IT-centric security measures are often inadequate for the Operational Technology (OT) environment due to stringent real-time and [...] Read more.
Industrial Control Systems (ICSs) are fundamental to critical infrastructure, yet they face increasing cybersecurity threats, particularly data integrity attacks like replay and data forgery attacks. Traditional IT-centric security measures are often inadequate for the Operational Technology (OT) environment due to stringent real-time and reliability requirements. This paper proposes an endogenous security defense mechanism based on the Luenberger observer and residual analysis. By embedding a mathematical model of the physical process into the control system, this approach enables real-time state estimation and anomaly detection. We model the ICS using a linear state-space representation and design a Luenberger observer to generate a residual signal, which is the difference between the actual sensor measurements and the observer’s predictions. Under normal conditions, this residual is minimal, but it deviates significantly during a replay attack. We formalize the system model, observer design, and attack detection algorithm. The effectiveness of the proposed method is validated through a simulation of an ICS under a replay attack. The results demonstrate that the residual-based approach can detect the attack promptly and effectively, providing a lightweight yet robust solution for enhancing ICS security. Full article
(This article belongs to the Special Issue Research and Application of Network and System Security)
20 pages, 1330 KiB  
Article
A Comprehensive Approach to Rustc Optimization Vulnerability Detection in Industrial Control Systems
by Kaifeng Xie, Jinjing Wan, Lifeng Chen and Yi Wang
Mathematics 2025, 13(15), 2459; https://doi.org/10.3390/math13152459 - 30 Jul 2025
Viewed by 321
Abstract
Compiler optimization is a critical component for improving program performance. However, the Rustc optimization process may introduce vulnerabilities due to algorithmic flaws or issues arising from component interactions. Existing testing methods face several challenges, including high randomness in test cases, inadequate targeting of [...] Read more.
Compiler optimization is a critical component for improving program performance. However, the Rustc optimization process may introduce vulnerabilities due to algorithmic flaws or issues arising from component interactions. Existing testing methods face several challenges, including high randomness in test cases, inadequate targeting of vulnerability-prone regions, and low-quality initial fuzzing seeds. This paper proposes a test case generation method based on large language models (LLMs), which utilizes prompt templates and optimization algorithms to generate a code relevant to specific optimization passes, especially for real-time control logic and safety-critical modules unique to the industrial control field. A vulnerability screening approach based on static analysis and rule matching is designed to locate potential risk points in the optimization regions of both the MIR and LLVM IR layers, as well as in unsafe code sections. Furthermore, the targeted fuzzing strategy is enhanced by designing seed queues and selection algorithms that consider the correlation between optimization areas. The implemented system, RustOptFuzz, has been evaluated on both custom datasets and real-world programs. Compared with state-of-the-art tools, RustOptFuzz improves vulnerability discovery capabilities by 16%–50% and significantly reduces vulnerability reproduction time, thereby enhancing the overall efficiency of detecting optimization-related vulnerabilities in Rustc, providing key technical support for the reliability of industrial control systems. Full article
(This article belongs to the Special Issue Research and Application of Network and System Security)
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