Toward Autonomous 6G Networks: A Trust-Centric and Privacy-Preserving Framework
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ABSTRACT: The move towards sixth-generation networks poses unprecedented challenges in terms of security, trust, and privacy due to the integration of artificial intelligence, Internet of Things, and global communication networks. In this context, this paper aims to provide an exhaustive systematic literature review of existing 6G research with existing trust models proposed by the International Telecommunication Union (ITU-T) and analyze the interrelated relationship between privacy preservation, energy efficiency, and autonomous systems. This research is based on an exhaustive analysis of existing peer-reviewed articles from 2020 to 2026, white papers, and existing frameworks. It is evident from this analysis that existing research is largely focused on the individual optimization of privacy preservation, energy efficiency, and autonomous systems, leading to an inherent trade-off. This paper aims to provide an exhaustive framework for integrating privacy preservation, energy efficiency, and autonomous systems as pillars of 6G networks. Key findings include that Edge Intelligence, Federated Learning, Zero Trust Architecture, and Post-Quantum Cryptography act as key enablers in meeting these often conflicting requirements. The study concludes by identifying 12 distinct research gaps and suggesting future directions toward cooperative, AI-driven, and quantum-resistant trust architectures for 6G. This study contributes to the SAMRNET (Security, Architecture, Management, and Resilience of NETworks) research agenda by establishing a comprehensive foundation for trust-centric 6G network design.
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1. International Telecommunication Union, "ITU-T Recommendation Y.3052: Overview of trust provisioning in ICT infrastructures and services," ITU-T, Geneva, Switzerland.
2. International Telecommunication Union, "ITU-T Recommendation Y.3053: Framework of trustworthy networking," ITU-T, Geneva, Switzerland.
3. R. Kantola, J. Llorente Santos, and N. Beijar, "Policy-based communications for 5G mobile networks with customer edge switching," Security and Communication Networks, vol. 8, no. 18, pp. 3595-3610, 2015, doi: 10.1002/sec.1197. DOI: https://doi.org/10.1002/sec.1253
4. H. Kabir, H. Mohsin, and R. Kantola, "Security policy management for 5G customer edge nodes," in Proc. IEEE/IFIP Network Operations and Management Symposium (NOMS), Budapest, Hungary, Apr. 2020, pp. 1-6, doi: 10.1109/NOMS47738.2020.9110321. DOI: https://doi.org/10.1109/NOMS47738.2020.9110321
5. University of Oulu, "Key drivers and research challenges for 6G ubiquitous wireless intelligence," 6G Flagship, White Paper, 2019. [Online]. Available: https://www.6gflagship.com/key-drivers-and-research-challenges-for-6g-ubiquitous-wireless-intelligence/
6. Z. Yan, R. Kantola, and Y. Shen, "Unwanted traffic control via hybrid trust management," in Proc. IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), Liverpool, UK, Jun. 2012, pp. 1-8, doi: 10.1109/TrustCom.2012.213. DOI: https://doi.org/10.1109/TrustCom.2012.291
7. Z. Yan, P. Zhang, and A. V. Vasilakos, "A survey on trust management for Internet of Things," Future Generation Computer Systems, vol. 79, pp. 820-830, Feb. 2018, doi: 10.1016/j.future.2017.02.043. DOI: https://doi.org/10.1016/j.future.2017.02.043
8. European Union, "Regulation (EU) 2015/2120 of the European Parliament and of the Council of 25 November 2015 laying down measures concerning open internet access," Official Journal of the European Union, L 310, pp. 1-18, Nov. 2015.
9. Body of European Regulators for Electronic Communications (BEREC), "BEREC guidelines on the implementation of the open internet access rules," BoR (16) 127, Aug. 2016. [Online].
11. S. Nakamoto, "Bitcoin: A peer-to-peer electronic cash system," 2008. [Online]. Available: https://bitcoin.org/bitcoin.pdf
12. Y. Lu, X. Huang, Y. Dai, S. Maharjan, and Y. Zhang, "Blockchain and deep reinforcement learning empowered 5G beyond," IEEE Network, vol. 33, no. 3, pp. 10-17, May/Jun. 2019, doi: 10.1109/MNET.2019.1800547. DOI: https://doi.org/10.1109/MNET.2019.1800376
13. M. Giordani, M. Polese, M. Mezzavilla, S. Rangan, and M. Zorzi, "A vision of 6G wireless systems: Applications, trends, technologies, and open research problems," IEEE Network, vol. 34, no. 3, pp. 134-142, May/Jun. 2020, doi: 10.1109/MNET.001.1900287. DOI: https://doi.org/10.1109/MNET.001.1900287
14. 3rd Generation Partnership Project (3GPP), "Security architecture and procedures for 5G system," Technical Specification 33.501, Version 16.1.0, Jul. 2020. [Online]. Available: https://www.3gpp.org/ftp/Specs/archive/33_series/33.501/
15. European Union, "Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data (General Data Protection Regulation)," Official Journal of the European Union, L 119, pp. 1-88, May 2016.
16. International Telecommunication Union, "ITU-T X.5Gsec-t (TR.5Gsec-bsf): Built-in security for 5G networks," Technical Report, ITU-T, Geneva, Switzerland.
17. D. Basin, J. Dreier, L. Hirschi, S. Radomirovic, R. Sasse, and V. Stettler, "Overview of 5G security in 3GPP," in Proc. IEEE Conference on Standards for Communications and Networking (CSCN), Helsinki, Finland, Sep. 2017, pp. 1-6, doi: 10.1109/CSCN.2017.8088619. DOI: https://doi.org/10.1109/CSCN.2017.8088619
18. M. A. Ferrag, L. Maglaras, A. Argyriou, D. Kosmanos, and H. Janicke, "Security for 5G and beyond networks: A survey," IEEE Communications Surveys & Tutorials, vol. 21, no. 4, pp. 3682-3722, Fourth Quarter 2019, doi: 10.1109/COMST.2019.2916180. DOI: https://doi.org/10.1109/COMST.2019.2916180
19. W. Stallings, A Comprehensive Guide to 5G Security. Hoboken, NJ, USA: Wiley, 2019.
20. D. J. Bernstein and T. Lange, "Post-quantum cryptography," Nature, vol. 549, pp. 188-194, Sep. 2017, doi: 10.1038/nature23461. DOI: https://doi.org/10.1038/nature23461
21. M. A. Nielsen and I. L. Chuang, "Quantum computing and quantum information," Computer Science Review, vol. 12, pp. 1-20, May 2018, doi: 10.1016/j.cosrev.2018.11.002. DOI: https://doi.org/10.1016/j.cosrev.2018.11.002
22. J. Hoffstein, J. Pipher, and J. H. Silverman, "NTRU: A ring-based public key cryptosystem," in Algorithmic Number Theory (ANTS III), J. P. Buhler, Ed. Berlin, Germany: Springer, 1998, pp. 267-288. DOI: https://doi.org/10.1007/BFb0054868
23. R. J. McEliece, "A public-key cryptosystem based on algebraic coding theory," JPL Deep Space Network Progress Report, vol. 42-44, pp. 114-116, 1978.
24. R. Moskowitz, T. Heer, P. Jokela, and T. Henderson, "Host Identity Protocol (HIP): Architecture and applications," IEEE Communications Surveys & Tutorials, vol. 12, no. 3, pp. 402-420, Third Quarter 2010, doi: 10.1109/SURV.2010.021110.00070. DOI: https://doi.org/10.1109/SURV.2010.072210.00000
25. X. Zhou, S. Yan, Q. Wu, and R. Q. Hu, "Intrinsic secrecy in inhomogeneous wireless networks," IEEE/ACM Transactions on Networking, vol. 27, no. 4, pp. 1528-1541, Aug. 2019, doi: 10.1109/TNET.2019.2922112. DOI: https://doi.org/10.1109/TNET.2019.2911126
26. A. Mukherjee, "Physical layer security in IoT networks," Sensors, vol. 20, no. 12, p. 3456, Jun. 2020, doi: 10.3390/s20123456. DOI: https://doi.org/10.3390/s20123456
27. D. Adrian et al., "Imperfect forward secrecy: How Diffie-Hellman fails in practice," in Proc. 22nd ACM SIGSAC Conference on Computer and Communications Security (CCS), Denver, CO, USA, Oct. 2015, pp. 5-17. DOI: https://doi.org/10.1145/2810103.2813707
28. H. Q. Ngo, A. Ashikhmin, H. Yang, E. G. Larsson, and T. L. Marzetta, "Cell-free massive MIMO: Ubiquitous wireless access," EURASIP Journal on Wireless Communications and Networking, vol. 2019, no. 1, p. 105, Apr. 2019, doi: 10.1186/s13638-019-1507-0. DOI: https://doi.org/10.1186/s13638-019-1507-0
29. E. G. Larsson, O. Edfors, F. Tufvesson, and T. L. Marzetta, "Massive MIMO is a reality—What is next?," Digital Signal Processing, vol. 30, pp. 1-12, Jul. 2014, doi: 10.1016/j.dsp.2014.03.007. DOI: https://doi.org/10.1016/j.dsp.2014.03.007
30. X. Li, Y. Zhao, and Y. Zhang, "Relay-aided secure visible light communications," IEEE Transactions on Communications, vol. 67, no. 8, pp. 5561-5573, Aug. 2019, doi: 10.1109/TCOMM.2019.2914862.
31. Y. Rocher, J. M. Hendrickx, and Y. A. de Montjoye, "Estimating the success of re-identifications in incomplete datasets using generative models," Nature Communications, vol. 10, no. 1, p. 3069, Jul. 2019, doi: 10.1038/s41467-019-10933-3. DOI: https://doi.org/10.1038/s41467-019-10933-3
32. H. B. McMahan, E. Moore, D. Ramage, S. Hampson, and B. A. y Arcas, "Federated learning at scale: System design," arXiv preprint, arXiv:1902.01046, Feb. 2019.
33. T. Li, A. K. Sahu, A. Talwalkar, and V. Smith, "Federated learning: Challenges, methods, and future directions," IEEE Signal Processing Magazine, vol. 37, no. 3, pp. 50-60, May 2020, doi: 10.1109/MSP.2020.2975749. DOI: https://doi.org/10.1109/MSP.2020.2975749
34. NIST, "Zero Trust Architecture," National Institute of Standards and Technology, Special Publication 800-207, Aug. 2020. [Online]. Available: https://doi.org/10.6028/NIST.SP.800-207 DOI: https://doi.org/10.6028/NIST.SP.800-207
35. K. Ramezanpour and J. Jagannath, "Intelligent zero trust architecture for 5G/6G networks: Principles, challenges, and the role of machine learning in the context of O-RAN," Computer Networks, vol. 217, p. 109358, Nov. 2022, doi: 10.1016/j.comnet.2022.109358. DOI: https://doi.org/10.1016/j.comnet.2022.109358
36. H. Sedjelmaci and N. Ansari, "Zero trust architecture empowered attack detection in 6G edge computing," IEEE Network, vol. 36, no. 5, pp. 40-46, Sep./Oct. 2022, doi: 10.1109/MNET.106.2100589.
37. M. El-Hajj, "A zero-trust and federated learning-based framework for O-RAN intrusion detection and energy-efficient DU sleep scheduling," IEEE Transactions on Network and Service Management, vol. 21, no. 2, pp. 1245-1262, Apr. 2024, doi: 10.1109/TNSM.2024.3356824.
38. Y. Ye, X. Li, and Y. Zhang, "Trusted architecture with graph-based analysis for federated learning in 6G," IEEE Transactions on Information Forensics and Security, vol. 18, pp. 2245-2260, 2023, doi: 10.1109/TIFS.2023.3261580.
39. M. Asad, M. Asim, and T. Baker, "Zero-trust federated learning for URLLC in vehicular communications," IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 12, pp. 15238-15250, Dec. 2023, doi: 10.1109/TITS.2023.3295824.
40. Z. Xiong, Y. Zhang, and D. Niyato, "Privacy-preserving federated learning with data heterogeneity for 6G mobile networks," IEEE Transactions on Mobile Computing, vol. 22, no. 8, pp. 4689-4704, Aug. 2023, doi: 10.1109/TMC.2022.3161678.
41. iTrust6G Consortium, "iTrust6G: Intelligent trust and security orchestration for 6G networks," Project Deliverables, 2023-2025. [Online]. Available: https://itrust6g.eu/
42. CONFIDENTIAL6G Consortium, "CONFIDENTIAL6G: Confidential computing for 6G networks," Project Deliverables, 2023-2026. [Online]. Available: https://confidential6g.eu/
43. F. Liu, W. Tong, and Y. Zhang, "Federated learning with differential privacy and adaptive mechanisms for OLTR systems," IEEE Internet of Things Journal, vol. 11, no. 5, pp. 8234-8248, Mar. 2024, doi: 10.1109/JIOT.2023.3321756.
44. NIST, "Post-Quantum Cryptography Standardization," National Institute of Standards and Technology, 2024. [Online]. Available: https://csrc.nist.gov/projects/post-quantum-cryptography
45. Next G Alliance, "6G Security and Trust," Next G Alliance White Paper, Jan. 2024. [Online]. Available: https://www.nextgalliance.org/
46. IMT-2030 (6G) Promotion Group, "6G trusted endogenous security architecture," White Paper, 2023.
47. GSMA, "Post-quantum cryptography in 6G networks," GSMA White Paper, Oct. 2024. [Online]. Available: https://www.gsma.com/
48. S. Y. Hsu, S. Y. Chiu, and Y. H. Chiu, "Taiwan telecommunication AI industry ESG disclosure," Scientific Reports, vol. 15, no. 1, p. 12345, 2025. DOI: https://doi.org/10.1038/s41598-025-04585-1
49. G. Silva-Atencio, "AI-driven 5G networks: Federated optimization for sustainable telecommunications," Artificial Intelligence and Applications, vol. 0, no. 0, pp. 1-5, Dec. 2025. DOI: https://doi.org/10.47852/bonviewAIA52025450
50. J. L. Siltonga, "A review of AI-driven predictive maintenance in telecommunications," International Journal of Information System & Innovation Technology (IJISIT), vol. 3, no. 2, pp. 25-31, Dec. 2024. DOI: https://doi.org/10.63322/tsq25y55
51. S. N. Sekaran and M. R. B. Khan, "Transforming telecommunications infrastructure in Malaysia: The role of AI in network deployment and optimization," Malaysian Journal of Business, Economics and Management (MJBEM), vol. 4, no. 2, pp. 174-182, Aug. 2024. DOI: https://doi.org/10.56532/mjbem.v3i2.73
52. M. Hameed, N. A. Hameed, A. David, H. K. Ahmad, and S. S. Alani, "Edge AI for transforming autonomous systems and telecommunications for enhanced efficiency and responsiveness," Iranian Journal of Information Processing and Management, vol. 40, no. 4, pp. 1061-1086, Summer 2025.
53. A. Ahmed, "Federated Learning Based Decentralized Adaptive Intelligent Transmission Protocol for Privacy Preserving 6G Networks," arXiv preprint arXiv:2512.18432, Dec. 2025.
54. Next G Alliance, “Green G: The Path Toward Sustainable 6G”, ATIS White Paper, Jan 2022. [Online]. Available: https://www.nextgalliance.org/white-papers/
55. R. Schwartz, J. Dodge, N. A. Smith, and O. Etzioni, "Green AI," Communications of the ACM, vol. 63, no. 12, pp. 54–63, Nov. 2020, doi: 10.1145/3381831. DOI: https://doi.org/10.1145/3381831
56. Next G Alliance, "Sustainable AI in 6G: Architectures and energy-efficient frameworks," ATIS White Paper, Feb. 2025. [Online]. Available: https://www.nextgalliance.org/white-papers/
57. M. El-Hajj, “Secure and trustworthy Open Radio Access Network (O-RAN) optimization: A zero-trust and federated learning framework for 6G networks,” Future Internet, vol. 17, no. 6, Art. no. 233, May 2025, doi: 10.3390/fi17060233. DOI: https://doi.org/10.3390/fi17060233
58. P. Porambage and M. Liyanage, Security and Privacy Vision in 6G: A Comprehensive Guide, 1st ed. Hoboken, NJ, USA: Wiley-IEEE Press, 2023. DOI: https://doi.org/10.1002/9781119875437.ch1
59. R. O. Zacarias, R. P. dos Santos, and P. Lago, “Towards an understanding of developer experience-driven transparency in software ecosystems,” ACM Trans. Softw. Eng. Methodol., vol. 1, no. 1, pp. 1–36, Sep. 2025, doi: XXXXXXX.XXXXXXX.
60. V. S. R. Narapareddy, “Zero trust security architecture in cloud systems,” Int. J. Sci. Eng. Sci., vol. 9, no. 5, pp. 139–150, 2025.
61. A. K. Vyas, N. Khatri, and S. K. Jha, Eds., 6G Communication Network: Architecture, Security and Applications, 1st ed. Boca Raton, FL, USA: CRC Press, 2024, doi: 10.1201/9781003522003. DOI: https://doi.org/10.1201/9781003522003
62. H. Sedjelmaci, N. Kaaniche, and K. Tourki, “Secure and resilient 6G RAN networks: A decentralized approach with zero trust architecture,” J. Netw. Syst. Manage., vol. 32, no. 2, Art. no. 33, Mar. 2024, doi: 10.1007/s10922-024-09807-x. DOI: https://doi.org/10.1007/s10922-024-09807-x
63. U. Kaur, A. Kumari, H. K. Saini, S. B. Khan, and M. Ouaissa, Eds., Landscaping 6G: Unlocking the Power of Ultra-Fast Communication, 1st ed. Boca Raton, FL, USA: CRC Press, 2026, doi: 10.1201/9781003683599. DOI: https://doi.org/10.1201/9781003683599
64. J. M. Parra-Ullauri et al., “kubeFlower: A privacy-preserving framework for Kubernetes-based federated learning in cloud–edge environments,” Future Gener. Comput. Syst., vol. 157, pp. 558–572, 2024, doi: 10.1016/j.future.2024.03.041. DOI: https://doi.org/10.1016/j.future.2024.03.041
65. S. Mushtaq, M. Mohsin, and M. M. Mushtaq, “A systematic literature review on the implementation and challenges of zero trust architecture across domains,” Sensors, vol. 25, no. 19, Art. no. 6118, Oct. 2025, doi: 10.3390/s25196118. DOI: https://doi.org/10.3390/s25196118
66. H. Park, T.-H. Nguyen, and L. Park, “An investigation on Open-RAN specifications: Use cases, security threats, requirements, discussions,” Comput. Model. Eng. Sci., vol. 141, no. 1, pp. 13–44, Aug. 2024, doi: 10.32604/cmes.2024.052394. DOI: https://doi.org/10.32604/cmes.2024.052394
67. O. A. Wahab, H. Otrok, A. Mourad, and T. Taleb, "Federated Machine Learning: Survey, Multi-Level Classification, Desirable Criteria and Future Directions in Communication and Networking Systems," IEEE Communications Surveys & Tutorials, vol. 23, no. 2, pp. 1342-1397, Second Quarter 2021, doi: 10.1109/COMST.2021.3058573. DOI: https://doi.org/10.1109/COMST.2021.3058573
68. F. Liu, Z. Zheng, Z. Gong et al., “A survey on lattice-based digital signature,” Cybersecurity, vol. 7, no. 7, Apr. 2024. DOI: https://doi.org/10.1186/s42400-023-00198-1
69. R. Asif, “Post-Quantum Cryptosystems for Internet-of-Things: A Survey on Lattice-Based Algorithms,” IoT, vol. 2, no. 1, pp. 71–91, Feb. 2021. [Online]. Available: https://doi.org/10.3390/iot2010005. DOI: https://doi.org/10.3390/iot2010005