Cybersecurity and Data Protection: Modern Methods and New Applications

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

Deadline for manuscript submissions: 20 September 2025 | Viewed by 357

Special Issue Editors


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Guest Editor
Faculty of Informatics/Mathematics, Dresden University of Applied Sciences, 01069 Dresden, Germany
Interests: network security; railway security; security and safety; quantum communication; encryption schemes; performance engineering

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Guest Editor Assistant
Mathematics and Computer Science, University of Würzburg, Würzburg, Germany
Interests: network security; security and safety; encryption schemes; performance engineering; homomorphic encryption

Special Issue Information

Dear Colleagues,

We are pleased to announce this Special Issue of the journal Mathematics entitled “Cybersecurity and Data Protection: Modern Methods and New Applications”. This initiative focuses on advances in mathematical research and practical applications in cybersecurity and data protection, which have been attracting growing interest due to their critical role in addressing contemporary cyber threats. Recent developments in applied mathematics have significantly contributed to enhancing the security and resilience of systems across various domains, including finance, healthcare, critical infrastructure, communication networks, and information systems. A wide range of complex challenges have been effectively tackled, such as cryptographic algorithm design, threat detection, risk assessment, secure data sharing, privacy preservation, and the optimization of security protocols.

This Special Issue invites high-quality original research or review papers on modern methods and new applications in cybersecurity and data protection to address the practical challenges in the related areas. The topics of interest include, but are not limited to, the following list:

  1. Cryptographic Methods Development of novel encryption algorithms
  2. Threat Detection and Prevention Mathematical models for identifying malware and phishing attacks
  3. Privacy Preservation Differential privacy and its applications
  4. Risk Assessment and Management Quantitative risk assessment models
  5. Secure Data Sharing and Storage Methods for ensuring data integrity and confidentiality
  6. Optimization of Security Protocols Game theory applications in cybersecurity
  7. Artificial Intelligence in Cybersecurity Machine learning models for cyber threat intelligence
  8. Mathematical Foundations of Cybersecurity Theoretical analysis of security models
  9. Applications in Industry Cybersecurity challenges in IoT and smart devices
  10. Emerging Areas and Trends Quantum computing implications for cybersecurity.

Prof. Dr. Lukas Iffländer
Guest Editor

Thomas Prantl
Guest Editor Assistant

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Keywords

  • advances in post-quantum cryptography
  • secure key generation and distribution techniques
  • intrusion detection systems using advanced analytics
  • anomaly detection in large-scale networks
  • secure multiparty computation techniques
  • homomorphic encryption for secure data processing
  • vulnerability analysis frameworks
  • optimization of risk mitigation strategies
  • methods for secure cloud storage
  • secure sharing protocols for big data applications
  • resource optimization in security systems
  • benchmarking of security system performance
  • deep learning techniques for real-time threat detection
  • explainable AI in cybersecurity applications
  • graph theory and network security applications
  • chaos theory in cryptographic systems
  • securing critical infrastructure systems
  • data protection in healthcare and financial services
  • cyber-physical systems security
  • ethical and legal considerations in data protection

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Published Papers (1 paper)

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Research

25 pages, 1292 KiB  
Article
Trust Domain Extensions Guest Fuzzing Framework for Security Vulnerability Detection
by Eran Dahan, Itzhak Aviv and Michael Kiperberg
Mathematics 2025, 13(11), 1879; https://doi.org/10.3390/math13111879 - 4 Jun 2025
Viewed by 66
Abstract
The Intel® Trust Domain Extensions (TDX) encrypt guest memory and minimize host interactions to provide hardware-enforced isolation for sensitive virtual machines (VMs). Software vulnerabilities in the guest OS continue to pose a serious risk even as the TDX improves security against a [...] Read more.
The Intel® Trust Domain Extensions (TDX) encrypt guest memory and minimize host interactions to provide hardware-enforced isolation for sensitive virtual machines (VMs). Software vulnerabilities in the guest OS continue to pose a serious risk even as the TDX improves security against a malicious hypervisor. We suggest a comprehensive TDX Guest Fuzzing Framework that systematically explores the guest’s code paths handling untrusted inputs. Our method uses a customized coverage-guided fuzzer to target those pathways with random input mutations following integrating static analysis to identify possible attack surfaces, where the guest reads data from the host. To achieve high throughput, we also use snapshot-based virtual machine execution, which returns the guest to its pre-interaction state at the end of each fuzz iteration. We show how our framework reveals undiscovered vulnerabilities in device initialization procedures, hypercall error-handling, and random number seeding logic using a QEMU/KVM-based TDX emulator and a TDX-enabled Linux kernel. We demonstrate that a large number of vulnerabilities occur when developers implicitly rely on values supplied by a hypervisor rather than thoroughly verifying them. This study highlights the urgent need for ongoing, automated testing in private computing environments by connecting theoretical completeness arguments for coverage-guided fuzzing with real-world results on TDX-specific code. We discovered several memory corruption and concurrency weaknesses in the TDX guest OS through our coverage-guided fuzzing campaigns. These flaws ranged from nested #VE handler deadlocks to buffer overflows in paravirtual device initialization to faulty randomness-seeding logic. By exploiting these vulnerabilities, the TDX’s hardware-based memory isolation may be compromised or denial-of-service attacks may be made possible. Thus, our results demonstrate that, although the TDX offers a robust hardware barrier, comprehensive input validation and equally stringent software defenses are essential to preserving overall security. Full article
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