Zero-Trust Mechanisms for Securing Distributed Edge and Fog Computing in 6G Networks
The rapid advancement in 6G networks, driven by the proliferation of distributed edge and fog computing, has introduced unprecedented challenges in securing these decentralized architectures. Traditional security paradigms are inadequate for protecting the dynamic and heterogeneous environments of 6...
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MDPI AG
2025-04-01
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| Series: | Mathematics |
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| author | Abdulrahman K. Alnaim Ahmed M. Alwakeel |
| author_facet | Abdulrahman K. Alnaim Ahmed M. Alwakeel |
| author_sort | Abdulrahman K. Alnaim |
| collection | DOAJ |
| description | The rapid advancement in 6G networks, driven by the proliferation of distributed edge and fog computing, has introduced unprecedented challenges in securing these decentralized architectures. Traditional security paradigms are inadequate for protecting the dynamic and heterogeneous environments of 6G-enabled systems. In this context, we propose ZTF-6G (Zero-Trust Framework for 6G Networks), a novel model that integrates Zero-Trust principles to secure distributed edge and fog computing environments. Robust security is ensured by ZTF-6G by adopting a “never trust, always verify” approach, which comprises adaptive authentication, continuous verification, and fine-grained access control against all entities within the network. Within this context, our proposed framework makes use of Zero-Trust-based multi-layering that extends to AI-driven anomaly detection and blockchain-based identity management for the authentication and real-time monitoring of network interactions. Simulation results indicate that ZTF-6G is able to reduce latency by 77.6% (up to 2.8 ms, compared to the standard models’ 12.5 ms), improve throughput by 70%, and improve resource utilization by 41.5% (90% of utilization). Additionally, the trust score accuracy increased from 95% to 98%, energy efficiency improved by 22.2% (from 88% to 110% efficiency), and threat detection accuracy increased to 98%. Finally, the framework perfectly mitigated the insider threats by 85% and enforced a dynamic policy within 1.8 ms. ZTF-6G maintained a low latency while providing more resilience to insider threats, unauthorized access, and data breaches, which is a requirement of 6G networks. This research aims to lay a foundation for deploying Zero-Trust as an integral part of the next-generation networks which will face the security challenges of the distributed systems driven by 6G networks. |
| format | Article |
| id | doaj-art-e567fc35f619478c847bdce9e700bd63 |
| institution | DOAJ |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-e567fc35f619478c847bdce9e700bd632025-08-20T03:13:50ZengMDPI AGMathematics2227-73902025-04-01138123910.3390/math13081239Zero-Trust Mechanisms for Securing Distributed Edge and Fog Computing in 6G NetworksAbdulrahman K. Alnaim0Ahmed M. Alwakeel1Department of Management Information Systems, School of Business, King Faisal University, Hofuf 31982, Saudi ArabiaFaculty of Computers & Information Technology, University of Tabuk, Tabuk 71491, Saudi ArabiaThe rapid advancement in 6G networks, driven by the proliferation of distributed edge and fog computing, has introduced unprecedented challenges in securing these decentralized architectures. Traditional security paradigms are inadequate for protecting the dynamic and heterogeneous environments of 6G-enabled systems. In this context, we propose ZTF-6G (Zero-Trust Framework for 6G Networks), a novel model that integrates Zero-Trust principles to secure distributed edge and fog computing environments. Robust security is ensured by ZTF-6G by adopting a “never trust, always verify” approach, which comprises adaptive authentication, continuous verification, and fine-grained access control against all entities within the network. Within this context, our proposed framework makes use of Zero-Trust-based multi-layering that extends to AI-driven anomaly detection and blockchain-based identity management for the authentication and real-time monitoring of network interactions. Simulation results indicate that ZTF-6G is able to reduce latency by 77.6% (up to 2.8 ms, compared to the standard models’ 12.5 ms), improve throughput by 70%, and improve resource utilization by 41.5% (90% of utilization). Additionally, the trust score accuracy increased from 95% to 98%, energy efficiency improved by 22.2% (from 88% to 110% efficiency), and threat detection accuracy increased to 98%. Finally, the framework perfectly mitigated the insider threats by 85% and enforced a dynamic policy within 1.8 ms. ZTF-6G maintained a low latency while providing more resilience to insider threats, unauthorized access, and data breaches, which is a requirement of 6G networks. This research aims to lay a foundation for deploying Zero-Trust as an integral part of the next-generation networks which will face the security challenges of the distributed systems driven by 6G networks.https://www.mdpi.com/2227-7390/13/8/1239zero-trustedge computingfog computing6G networksblockchain securityadaptive authentication |
| spellingShingle | Abdulrahman K. Alnaim Ahmed M. Alwakeel Zero-Trust Mechanisms for Securing Distributed Edge and Fog Computing in 6G Networks Mathematics zero-trust edge computing fog computing 6G networks blockchain security adaptive authentication |
| title | Zero-Trust Mechanisms for Securing Distributed Edge and Fog Computing in 6G Networks |
| title_full | Zero-Trust Mechanisms for Securing Distributed Edge and Fog Computing in 6G Networks |
| title_fullStr | Zero-Trust Mechanisms for Securing Distributed Edge and Fog Computing in 6G Networks |
| title_full_unstemmed | Zero-Trust Mechanisms for Securing Distributed Edge and Fog Computing in 6G Networks |
| title_short | Zero-Trust Mechanisms for Securing Distributed Edge and Fog Computing in 6G Networks |
| title_sort | zero trust mechanisms for securing distributed edge and fog computing in 6g networks |
| topic | zero-trust edge computing fog computing 6G networks blockchain security adaptive authentication |
| url | https://www.mdpi.com/2227-7390/13/8/1239 |
| work_keys_str_mv | AT abdulrahmankalnaim zerotrustmechanismsforsecuringdistributededgeandfogcomputingin6gnetworks AT ahmedmalwakeel zerotrustmechanismsforsecuringdistributededgeandfogcomputingin6gnetworks |