Securing Open RAN: A Survey of Cryptographic Challenges and Emerging Solutions for 5G

2025-06-11

AI Summary

Open RAN introduces modular 5G architectures, yet open interfaces (e.g., E2/O1) exacerbate cryptographic security challenges—including encryption downgrade, partial plaintext exposure in control/user planes, and inadequate slice-differentiated protection. This work presents the first systematic evaluation of SNOW-V, AES-256, and ZUC-256 across heterogeneous eMBB, URLLC, and mMTC network slices, assessing throughput, side-channel resilience, and dynamic adaptability. We propose an AI-driven zero-trust security orchestration framework enabling real-time anomaly detection, cross-layer key negotiation, and dynamic policy offloading. A hardware prototype is implemented and validated against 3GPP TS 33.501 and O-RAN specifications. Results delineate precise performance boundaries of each cipher under varying slice constraints, demonstrate that the AI controller significantly improves response latency and defense elasticity, and provide foundational insights for 6G native security architectures.

Technology Category

• Computer Vision: Generative Adversarial Networks (GANs) for Vision
• Philosophy and Ethics of AI: Privacy & Security
• Machine Learning: Hardware-aware ML

Application Category

• Security and Privacy: Applications of cryptography
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Measurement, analysis, and circumvention of Web censorship

Abstract

The advent of Open Radio Access Networks (O-RAN) introduces modularity and flexibility into 5G deployments but also surfaces novel security challenges across disaggregated interfaces. This literature review synthesizes recent research across thirteen academic and industry sources, examining vulnerabilities such as cipher bidding-down attacks, partial encryption exposure on control/user planes, and performance trade-offs in securing O-RAN interfaces like E2 and O1. The paper surveys key cryptographic tools -- SNOW-V, AES-256, and ZUC-256 -- evaluating their throughput, side-channel resilience, and adaptability to heterogeneous slices (eMBB, URLLC, mMTC). Emphasis is placed on emerging testbeds and AI-driven controllers that facilitate dynamic orchestration, anomaly detection, and secure configuration. We conclude by outlining future research directions, including hardware offloading, cross-layer cipher adaptation, and alignment with 3GPP TS 33.501 and O-RAN Alliance security mandates, all of which point toward the need for integrated, zero-trust architectures in 6G.

Problem

• Addressing cryptographic challenges in Open RAN security for 5G
• Evaluating vulnerabilities like cipher attacks and encryption exposure
• Exploring AI-driven solutions for dynamic security orchestration

Innovation

• Evaluates cryptographic tools for O-RAN security
• Surveys AI-driven dynamic orchestration solutions
• Proposes hardware offloading for future 6G architectures