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

Hyeonsoo Yu; Hwankuk Kim

doi:10.32604/cmes.2026.082095

January 1, 2026Computer Modeling in Engineering & SciencesOpen Access

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

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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.

Implication

Evaluates anomaly detection effectiveness of AI-based IDS xApp in O-RAN, suggesting improved security solutions.

Abstract

The introduction of the Open Radio Access Network (O-RAN) architecture enhances network flexibility but introduces novel security threats targeting open interfaces and the RAN Intelligent Controller (RIC). Particularly in the... | Find, read and cite all the research you need on Tech Science Press

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Cite This Study

Yu et al. (2026) studied this question.

synapsesocial.com/papers/6a1bd0845783ba022b6fc3bb https://doi.org/10.32604/cmes.2026.082095

View Full Paper

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

Key Points

Implication

Abstract

Discussion

Cite This Study

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

Key Points

Implication

Abstract

Discussion

Cite This Study

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