Synergistic Solution: IDS and Scheduler Harmony for Secure 5G Radio Resources

The diverse range of applications in 5G networks introduces novel security challenges, particularly due to the high volume of transmitted packets. The proliferation of devices also increases their vulnerability to various security threats. Among these, Distributed Denial of Service (DDoS) attacks stand out as the most common in 5 G environments. Such attacks create a single point of failure by overwhelming the central base station with malicious traffic, leading to degradation in the quality of service for critical applications, especially those reliant on realtime responsiveness. The inundation of suspicious traffic hampers legitimate devices from fulfilling their tasks effectively. While traditional security measures, including Intrusion Detection Systems (IDS), are deployed to mitigate these threats, they often detect suspicious traffic only after it has reached the scheduler and resource allocation process. To address this limitation, we propose in this paper a novel architecture which integrates a filtering block and a Radio Resource Allocation Block (RRAB) to safeguard 5G radio resources. By employing unsupervised learning, the proposed architecture exhibits promising results in distinguishing between legitimate and illegitimate devices. Enhanced filtering mechanisms and prioritization tools contribute to a comprehensive mitigation strategy, bolstering the security and resilience of 5 G networks against evolving cyber threats.The implementation of clustering models, such as K-means and DBSCAN, effectively identifies patterns of unauthorized usage, with the DBSCAN model achieving high homogeneity (0.3161) and a V-measure of 0.2245. This comprehensive approach improves the quality of service for delay-sensitive applications and bolsters the security and resilience of 5 G networks against evolving cyber threats.