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Radio Access Network Anomalous State Detection Dataset

This project [1] produced two types of data: Working Data and Derived Data. The Working Data includes raw measurements collected from a Radio Access Network (RAN) utilizing commercial-off-the-shelf (COTS) hardware. These measurements were gathered at multiple layers of the Long-Term Evolution (LTE) protocol stack within the RAN, in both a baseline state with encrypted data and an anomalous state with encryption disabled. The data is provided in comma-separated value (.csv) format.The Working Data was then processed into Derived Data using Python 3 scripts that performed statistical analyses to explore data distributions. The Derived Data is also available in .csv files. Additionally, human-readable spreadsheets are included, offering measurement notes and definitions related to the Working Data. Please note that the data set is divided into three distinct tranches, or sections, in alignment with the project's design of experiment.[1] M. Frey, T. Evans, A. Folz, M. Gregg, J. Quimby, J. Rezac. ?Anomalous state detection in radio access networks: A proof-of-concept.? Journal of Network and Computer Applications. Volume 231, 2024, https://doi.org/10.1016/j.jnca.2024.103979.

About this Dataset

Updated: 2025-04-06
Metadata Last Updated: 2024-07-05 00:00:00
Date Created: N/A
Data Provided by:
Dataset Owner: N/A

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Table representation of structured data
Title Radio Access Network Anomalous State Detection Dataset
Description This project [1] produced two types of data: Working Data and Derived Data. The Working Data includes raw measurements collected from a Radio Access Network (RAN) utilizing commercial-off-the-shelf (COTS) hardware. These measurements were gathered at multiple layers of the Long-Term Evolution (LTE) protocol stack within the RAN, in both a baseline state with encrypted data and an anomalous state with encryption disabled. The data is provided in comma-separated value (.csv) format.The Working Data was then processed into Derived Data using Python 3 scripts that performed statistical analyses to explore data distributions. The Derived Data is also available in .csv files. Additionally, human-readable spreadsheets are included, offering measurement notes and definitions related to the Working Data. Please note that the data set is divided into three distinct tranches, or sections, in alignment with the project's design of experiment.[1] M. Frey, T. Evans, A. Folz, M. Gregg, J. Quimby, J. Rezac. ?Anomalous state detection in radio access networks: A proof-of-concept.? Journal of Network and Computer Applications. Volume 231, 2024, https://doi.org/10.1016/j.jnca.2024.103979.
Modified 2024-07-05 00:00:00
Publisher Name National Institute of Standards and Technology
Contact mailto:[email protected]
Keywords Anomalous state detection , cellular communication security , measurement stability , metrology , multi-feature detection , multi-layer architecture , radio access network.
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