An Open-RAN Testbed for Detecting and Mitigating Radio-Access Anomalies
- URL: http://arxiv.org/abs/2503.10255v1
- Date: Thu, 13 Mar 2025 11:10:29 GMT
- Title: An Open-RAN Testbed for Detecting and Mitigating Radio-Access Anomalies
- Authors: Hanna Bogucka, Marcin Hoffmann, Paweł Kryszkiewicz, Łukasz Kułacz,
- Abstract summary: This paper presents the Open Radio Access Net-work (O-RAN) testbed for secure radio access.<n>We discuss radio-originating attack detection and mitigation methods based on anomaly detection and how they can be implemented as specialized applications (xApps) in this testbed.
- Score: 2.5749046466046903
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: This paper presents the Open Radio Access Net-work (O-RAN) testbed for secure radio access. We discuss radio-originating attack detection and mitigation methods based on anomaly detection and how they can be implemented as specialized applications (xApps) in this testbed. We also pre-sent illustrating results of the methods applied in real-world scenarios and implementations.
Related papers
- Superpowering Open-Vocabulary Object Detectors for X-ray Vision [53.07098133237041]
Open-vocabulary object detection (OvOD) is set to revolutionize security screening by enabling systems to recognize any item in X-ray scans.
We propose RAXO, a framework that repurposes off-the-shelf RGB OvOD detectors for robust X-ray detection.
RAXO builds high-quality X-ray class descriptors using a dual-source retrieval strategy.
arXiv Detail & Related papers (2025-03-21T11:54:16Z) - Open Set RF Fingerprinting Identification: A Joint Prediction and Siamese Comparison Framework [37.79439245394741]
We propose a joint radio frequency fingerprint prediction and siamese comparison (JRFFP-SC) framework for open set recognition.<n>The proposed JRFFP-SC framework eliminates inter-class interference and effectively addresses the challenges associated with open set identification.
arXiv Detail & Related papers (2025-01-26T04:09:07Z) - What If We Had Used a Different App? Reliable Counterfactual KPI Analysis in Wireless Systems [52.499838151272016]
This paper addresses the problem of estimating the values of traffic that would have been obtained if a different app had been implemented by the RAN.<n>We propose a conformal-prediction-based counterfactual analysis method for wireless systems.
arXiv Detail & Related papers (2024-09-30T18:47:26Z) - Radio U-Net: a convolutional neural network to detect diffuse radio sources in galaxy clusters and beyond [0.0]
Radio interferometric images of diffuse sources present a challenge for image segmentation tasks.
We introduce Radio U-Net, a fully convolutional neural network based on the U-Net architecture.
Radio U-Net is designed to detect faint and extended sources in radio surveys.
arXiv Detail & Related papers (2024-08-20T14:03:21Z) - RADIA -- Radio Advertisement Detection with Intelligent Analytics [35.426591359304]
This study investigates a novel automated radio advertisement detection technique incorporating advanced speech recognition and text classification algorithms.
RadIA's approach surpasses traditional methods by eliminating the need for prior knowledge of the broadcast content.
Experimental results show that the resulting model, trained on carefully segmented and tagged text data, achieves an F1-macro score of 87.76 against a theoretical maximum of 89.33.
arXiv Detail & Related papers (2024-03-06T08:34:28Z) - On the Universal Adversarial Perturbations for Efficient Data-free
Adversarial Detection [55.73320979733527]
We propose a data-agnostic adversarial detection framework, which induces different responses between normal and adversarial samples to UAPs.
Experimental results show that our method achieves competitive detection performance on various text classification tasks.
arXiv Detail & Related papers (2023-06-27T02:54:07Z) - An anomaly detection approach for backdoored neural networks: face
recognition as a case study [77.92020418343022]
We propose a novel backdoored network detection method based on the principle of anomaly detection.
We test our method on a novel dataset of backdoored networks and report detectability results with perfect scores.
arXiv Detail & Related papers (2022-08-22T12:14:13Z) - Radio-Assisted Human Detection [61.738482870059805]
We propose a radio-assisted human detection framework by incorporating radio information into the state-of-the-art detection methods.
We extract the radio localization and identifer information from the radio signals to assist the human detection.
Experiments on the simulative Microsoft COCO dataset and Caltech pedestrian datasets show that the mean average precision (mAP) and the miss rate can be improved with the aid of radio information.
arXiv Detail & Related papers (2021-12-16T09:53:41Z) - OpenCSI: An Open-Source Dataset for Indoor Localization Using CSI-Based
Fingerprinting [73.9222625243696]
Fingerprint-based localization methods propose a solution to this problem, but rely on a radio map that is effort-intensive to acquire.
We automate the radio map acquisition phase using a software-defined radio (SDR) and a wheeled robot.
We describe first localization experiments on this radio map using a convolutional neural network to regress for location coordinates.
arXiv Detail & Related papers (2021-04-16T08:31:46Z) - Multi-stage Jamming Attacks Detection using Deep Learning Combined with
Kernelized Support Vector Machine in 5G Cloud Radio Access Networks [17.2528983535773]
This research focuses on deploying a multi-stage machine learning-based intrusion detection (ML-IDS) in 5G C-RAN.
It can detect and classify four types of jamming attacks: constant jamming, random jamming, jamming, and reactive jamming.
The final classification accuracy of attacks is 94.51% with a 7.84% false negative rate.
arXiv Detail & Related papers (2020-04-13T17:21:45Z) - Survey of Network Intrusion Detection Methods from the Perspective of
the Knowledge Discovery in Databases Process [63.75363908696257]
We review the methods that have been applied to network data with the purpose of developing an intrusion detector.
We discuss the techniques used for the capture, preparation and transformation of the data, as well as, the data mining and evaluation methods.
As a result of this literature review, we investigate some open issues which will need to be considered for further research in the area of network security.
arXiv Detail & Related papers (2020-01-27T11:21:05Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.