Zero Trust Security Architecture for 6G Open Radio Access Networks (ORAN)

被引：0

作者：

Moudoud, Hajar ^{[1
]}

Houda, Zakaria Abou El ^{[2
]}

Brik, Bouziane ^{[3
]}

机构：

[1] Université du Québec en Outaouais, Département d'Informatique et d'Ingénierie, Gatineau, J8X 3X7, QC

[2] INRS-EMT, Umr INRS-UQO, University of Quebec, Montreal, H3T 1J4, QC

[3] Sharjah University, College of Computing and Informatics, Computer Science Department, Sharjah

来源：

IEEE Networking Letters | 2024年 / 6卷 / 04期

关键词：

access control; authentication; blockchain; federated reinforcement learning; ORAN; zero-trust architecture (ZTA);

D O I：

10.1109/LNET.2024.3514357

中图分类号：

学科分类号：

摘要：

The evolution of Open Radio Access Networks (O-RAN) is crucial for the deployment and operation of 6G networks, providing flexibility and interoperability through its disaggregated and open architecture. However, this openness introduces new security issues. To address these challenges, we propose a novel Zero-Trust architecture tailored for ORAN (ZTORAN). ZTORAN includes two main modules: (1) A blockchain-based decentralized trust management system for secure verification, authentication, and dynamic access control of xApps; and (2) A threat detection module that uses Federated Multi-Agent Reinforcement Learning (FMARL) to monitor network activities continuously and detects anomalies within the ORAN ecosystem. Through comprehensive simulations and evaluations, we demonstrate the effectiveness of ZTORAN in providing a resilient and secure framework for next-generation wireless networks. © 2019 IEEE.

引用

页码：272 / 275

页数：3

共 13 条

[1]

Schwenteck P., Nguyen G.T., Boche H., Kellerer W., Fitzek F.H.P., 6G perspective of mobile network operators, manufacturers, and verticals, IEEE Netw. Lett., 5, 3, pp. 169-172, (2023)

[2]

Corici M., Eichhorn F., Magedanz T., Organic 6G continuum architecture: A uniform control plane across devices, radio, and core, IEEE Netw. Lett., 6, 1, pp. 11-15, (2024)

[3]

Polese M., Et al., Empowering the 6G cellular architecture with open RAN, IEEE J. Sel. Areas Commun., 42, 2, pp. 245-262, (2024)

[4]

Roy S., Chergui H., Verikoukis C., Toward bridging the FL performance-explainability tradeoff: A trustworthy 6G RAN slicing usecase, IEEE Trans. Veh. Technol., 73, 7, pp. 10529-10538, (2024)

[5]

Ghafouri N., Vardakas J.S., Ramantas K., Verikoukis C., A multi-level deep RL-based network slicing and resource management for O-RAN-based 6G cell-free networks, IEEE Trans. Veh. Technol., 73, 11, pp. 17472-17484, (2024)

[6]

Polese M., Bonati L., D'Oro S., Basagni S., Melodia T., Understanding O-RAN: Architecture, interfaces, algorithms, security, and research challenges, IEEE Commun. Surveys Tuts., 25, 2, pp. 1376-1411, (2023)

[7]

Groen J., Et al., Securing ORAN open interfaces, IEEE Trans. Mobile Comput., submitted for publication

[8]

Houda Z.A.E., Moudoud H., Brik B., Federated deep reinforcement learning for efficient jamming attack mitigation in O-RAN, IEEE Trans. Veh. Technol., 73, 7, pp. 9334-9343, (2024)

[9]

Moudoud H., Cherkaoui S., Enhancing open RAN security with zero trust and machine learning, Proc. IEEE Glob. Commun. Conf. (GLOBECOM), pp. 2772-2777, (2023)

[10]

Jiang H., Chang H., Mukherjee S., Van Der Merwe J., OZTrust: An O-RAN zero-trust security system, Proc. IEEE Conf. Netw. Funct. Virtualization Softw. Defin. Netw. (NFV-SDN), pp. 129-134, (2023)

← 1 2 →