An Exploration of Real-Time Intrusion Detection and Prevention Systems for Next Generation Networks

Abstract

Network security is facing new difficulties as a result of the development of 5G and other networks as well as software-defined networking (SDN). As the volume and complexity of network traffic increase, so does the risk of cyber threats and attacks. Designing and implementing a real-time Intrusion Detection and Prevention System (IDPS) for 5G and beyond SDNs requires addressing several challenges. These challenges include the high data rate and volume of traffic, the distributed and dynamic nature of 5G and beyond networks, and the complexity of the SDN architecture. A global IDPS architecture should be created to address these issues, using methods based on machine learning to quickly identify and categorize intrusions. To allow actual time monitoring and avoidance, the IDPS should also work across all the SDN design layers and interact with the SDN router. The implementation of a real-time IDPS for 5G and beyond SDNs would enhance network security by enabling real-time detection and prevention of intrusions. This would reduce the risk of data breaches, network downtime, and other Cyber Security threats. Moreover, a real-time IDPS would allow network administrators to respond to intrusions quickly and effectively, minimizing the impact of cyber threats on network operations. The actual time detection and avoidance of intrusions system for 5G technology along with SDN is thoroughly reviewed in this paper.