Securing 5G Networks with AI-Driven Intrusion Detection: Safeguarding Next-Generation Communication Infrastructures

The emergence of 5G networks has changed communication infrastructures to provide high speed, extremely low latency, and support for massive device connectivity. Nevertheless, this evolution has come at a cost and opened up new attack vectors, putting emphasis on the need for strong security mechanisms. With the convergence of ICT and mobile technologies, new paradigms like 5G are proposed to provide efficient and reliable services that can address various application demands in real-time. Utilizing advanced AI techniques like deep learning, anomaly detection, and reinforcement learning, this framework is capable of detecting and countering potential threats in real time while evolving with the changing nature of attack patterns. It kickers off with delving into the distinct challenges of 5G network security, including decentralized architectures, network slicing and software defined networking (SDN) paradigms. The paper critiques traditional IDS and their shortcomings in the face of these challenges, particularly pointing at their lack of scalability or flexibility with a changing 5G framework. To fill this gap, the research proposes an AI-empowered IDS integrating real-time data processing, user behavior profiling, as well as deep-learning based multi-level detection ability. With the help of comprehensive simulations and experimental evaluations, the proposed frame offers superior performance in terms of detecting diverse cyber threats such as DoS attacks, signaling storms and unauthorized access. Experimental results show that the accuracy of detecting intrusive behavior is improved, the rate of false positive is reduced, and the latency is smaller compared with an average conventional IDS. The framework has the ability to be used in different 5G segments, from core to edge, and is scalable. With an emphasis on the role of AI in future-proofing communication systems, this study highlights what makes it transformational in ensuring protected communication networks. Finally, it provides recommendations on the integration of AI-driven IDS into 5G networks and potential future research directions to increase resilience against these threats, ultimately reinforcing the security and reliability of digital ecosystems worldwide.