Published Paper Details:

The deployment of 5G networks introduces a new era of communication technologies, provides higher data speeds, reduction in latency and enhanced connectivity. However, these advancements also increase significant concerns regarding security, especially with the increased attack surface and complexity inherent in 5G's architecture. Intrusion Detection and Prevention Systems (IDPS) are essential for safeguarding 5G networks against malicious threats and ensuring the integrity and availability of services. This paper surveys the state-of-the-art techniques for detecting and preventing in 5G environments, including both traditional and modern approaches. We discuss the role of machine learning and artificial intelligence in enhancing the detection capabilities of IDPS, as well as the challenges posed by the dynamic, distributed nature of 5G networks. Additionally, we explore the integration of IDPS with emerging 5G technologies such as network slicing, edge computing, and the Internet of Things (IoT), highlighting the potential for more adaptive and scalable security solutions. The paper also reviews key issues like real-time processing, scalability, and the need for privacy-preserving methods in intrusion detection. Finally, we identify research gaps and propose directions for future work to enhance the resilience of 5G networks.