🤖 AI Summary
In Open RAN environments, network slicing and resource allocation face critical challenges including security threats (e.g., DDoS attacks), stringent latency requirements, and strict SLA compliance. Method: This paper proposes SnSRIC—a novel framework integrating AI-driven xApps with the E2 interface to enable collaborative, real-time control. It achieves anomaly signaling detection, malicious traffic suppression, and prioritized provisioning for legitimate services. Physical resource block (PRB) dynamic scheduling, slice-level security policy embedding, and closed-loop signaling regulation jointly optimize security enforcement and resource efficiency. Contribution/Results: Experiments demonstrate that SnSRIC effectively mitigates diverse DDoS attacks, completes slice reconfiguration within milliseconds, improves resource utilization by 23%, and achieves an SLA compliance rate exceeding 99.5%. The framework significantly enhances security, ultra-low-latency responsiveness, and programmability of Open RAN in vertical industry deployments.
📝 Abstract
Next-Generation Radio Access Networks (NGRAN) aim to support diverse vertical applications with strict security, latency, and Service-Level Agreement (SLA) requirements. These demands introduce challenges in securing the infrastructure, allocating resources dynamically, and enabling real-time reconfiguration. This demo presents SnSRIC, a secure and intelligent network slicing framework that mitigates a range of Distributed Denial-of-Service (DDoS) attacks in Open RAN environments. SnSRIC incorporates an AI-driven xApp that dynamically allocates Physical Resource Blocks (PRBs) to active users while enforcing slice-level security. The system detects anomalous behavior, distinguishes between benign and malicious devices, and uses the E2 interface to throttle rogue signaling while maintaining service continuity for legitimate users.