Data

NF-BoT-IoT-v3

The University of Queensland
Associate Professor Marius Portmann (Aggregated by) Associate Professor Marius Portmann (Aggregated by) Dr Siamak Layeghy (Aggregated by) Dr Siamak Layeghy (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.48610/73c4ebc&rft.title=NF-BoT-IoT-v3&rft.identifier=RDM ID: db0187cc-1f78-4215-8e34-303364498866&rft.publisher=The University of Queensland&rft.description=This dataset is an enhanced version of NetFlow-based datasets, incorporating 53 extracted features that provide detailed insights into network flows. The dataset includes binary and multi-class labels, distinguishing between normal traffic and four different types of attacks. It is structured in CSV format, with each row representing a single network flow, labeled accordingly. One of the key aspects of this dataset is the inclusion of temporal features, which allow for a more detailed analysis of traffic over time. The dataset records precise timestamps for each flow, including start and end times, enabling a more structured understanding of flow duration and activity patterns. Additionally, it captures inter-packet arrival time (IAT) statistics, including minimum, maximum, average, and standard deviation values for both source-to-destination and destination-to-source packet transmissions.Note, there are minor changes to the dataset description in this data record, which is slightly different from the information in the download files description. The information presented in this data record is the most up-to-date.&rft.creator=Associate Professor Marius Portmann&rft.creator=Associate Professor Marius Portmann&rft.creator=Dr Siamak Layeghy&rft.creator=Dr Siamak Layeghy&rft.date=2025&rft_rights= http://guides.library.uq.edu.au/deposit_your_data/terms_and_conditions&rft_subject=eng&rft_subject=Cybersecurity and privacy&rft_subject=INFORMATION AND COMPUTING SCIENCES&rft.type=dataset&rft.language=English Access the data
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s4517659@student.uq.edu.au
School of Electrical Engineering and Computer Science

Full description

This dataset is an enhanced version of NetFlow-based datasets, incorporating 53 extracted features that provide detailed insights into network flows. The dataset includes binary and multi-class labels, distinguishing between normal traffic and four different types of attacks. It is structured in CSV format, with each row representing a single network flow, labeled accordingly. One of the key aspects of this dataset is the inclusion of temporal features, which allow for a more detailed analysis of traffic over time. The dataset records precise timestamps for each flow, including start and end times, enabling a more structured understanding of flow duration and activity patterns. Additionally, it captures inter-packet arrival time (IAT) statistics, including minimum, maximum, average, and standard deviation values for both source-to-destination and destination-to-source packet transmissions.Note, there are minor changes to the dataset description in this data record, which is slightly different from the information in the download files description. The information presented in this data record is the most up-to-date.

Issued: 2025

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Subjects
Cybersecurity and Privacy | Information and Computing Sciences | eng |

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local : UQ:289097

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