Performance Analysis of an AI-Based IDS xApp for Cyberattack Anomaly Detection in O-RAN Near-RT RIC

Key Points

• This research aims to assess the performance of an AI-based Intrusion Detection System (IDS) for detecting cyberattacks within the O-RAN architecture.
• Utilized an AI-based IDS xApp within the O-RAN Near-RT RIC framework.
• Conducted performance evaluation against various cyberattack scenarios.
• Analyzed detection rates, false positives, and response times.
• Achieved an anomaly detection rate of 92% with an average response time of 1.5 seconds.
• Reported a false positive rate of 3%, indicating high reliability of the system.
• Demonstrated significant improvement in security posture for RAN interfaces.