Implementing and Evaluating Security in O-RAN: Interfaces, Intelligence, and Platforms
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Abstract (arXiv)
The Open Radio Access Network (RAN) is a networking paradigm that builds on top of cloud-based, multi-vendor, open and intelligent architectures to shape the next generation of cellular networks for 5G and beyond. While this new paradigm comes with many advantages in terms of observatibility and reconfigurability of the network, it inevitably expands the threat surface of cellular systems and can potentially expose its components to several cyber attacks, thus making securing O-RAN networks a necessity. In this paper, we explore the security aspects of O-RAN systems by focusing on the specifications and architectures proposed by the O-RAN Alliance. We address the problem of securing O-RAN systems with a holistic perspective, including considerations on the open interfaces used to interconnect the different O-RAN components, on the overall platform, and on the intelligence used to monitor and control the network. For each focus area we identify threats, discuss relevant solutions to address these issues, and demonstrate experimentally how such solutions can effectively defend O-RAN systems against selected cyber attacks. This article is the first work in approaching the security aspect of O-RAN holistically and with experimental evidence obtained on a state-of-the-art programmable O-RAN platform, thus providing unique guideline for researchers in the field.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Apr 2023.
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Citing papers per year: 2023: 1; 2024: 3; 2025: 1; 2026: 2.
7 papers.
- 2023In-Context Learning for MIMO Equalization Using Transformer-Based Sequence Modelscited by 11
- 2024Cell-Free Multi-User MIMO Equalization via In-Context Learningcited by 8
- 2026ML-Enabled Open RAN: A Comprehensive Survey of Architectures, Challenges, and Opportunitiescited by 4
- 2024Towards Secure Intelligent O-RAN Architecture: Vulnerabilities, Threats and Promising Technical Solutions using LLMscited by 3
- 2025Rogue Cell: Adversarial Attack and Defense in Untrusted O-RAN Setup Exploiting the Traffic Steering xAppcited by 2
- 2026AutORAN: LLM-driven Natural Language Programming for Agile xApp Developmentcited by 1
- 2024TIMESAFE: Timing Interruption Monitoring and Security Assessment for Fronthaul Environmentscited by 0
- 2026ML-Enabled Open RAN: A Comprehensive Survey of Architectures, Challenges, and Opportunities27 Mar 2026
- 2026AutORAN: LLM-driven Natural Language Programming for Agile xApp Development19 Mar 2026
- 2025Rogue Cell: Adversarial Attack and Defense in Untrusted O-RAN Setup Exploiting the Traffic Steering xApp3 May 2025
- 2024TIMESAFE: Timing Interruption Monitoring and Security Assessment for Fronthaul Environments17 Dec 2024
- 2024Towards Secure Intelligent O-RAN Architecture: Vulnerabilities, Threats and Promising Technical Solutions using LLMs13 Nov 2024
- 2024Cell-Free Multi-User MIMO Equalization via In-Context Learning8 Apr 2024
- 2023In-Context Learning for MIMO Equalization Using Transformer-Based Sequence Models10 Nov 2023