🤖 AI Summary
This study addresses the critical threat posed by low-power, stealthy Msg1 interference attacks on the Random Access Channel (RACH), which can severely disrupt legitimate user access in 5G and beyond-5G mobile networks. For the first time, the authors integrate theoretical modeling with over-the-air experiments to develop an analytical framework that accurately predicts the impact of such interference on RACH performance. Leveraging the OpenAirInterface open-source platform and software-defined radio (SDR) hardware, they implement a practical attack prototype. Experimental results demonstrate that even extremely low-power interference can significantly impair user access, thereby validating the high fidelity of the proposed model and exposing the real-world vulnerability of 5G/B5G systems to this class of attack. The work highlights both the novelty and practical utility of the proposed methodology for security assessment in next-generation cellular networks.
📝 Abstract
Random Access Channel (RACH) jamming poses a critical security threat to 5G and beyond (B5G) networks. This paper presents an analytical model for predicting the impact of Msg1 jamming attacks on RACH performance. We use the OpenAirInterface (OAI) open-source user equipment (UE) to implement a Msg1 jamming attacker. Over-the-air experiments validate the accuracy of the proposed analytical model. The results show that low-power and stealthy Msg1 jamming can effectively block legitimate UE access in 5G/B5G systems.