This dataset is used for network anomaly detection and is based on the UGR16 dataset network traffic flows. We used June week 2 to 4 tensors generated from raw flow data to train the models. The dataset includes a set of tensors generated from the whole UGR’16 network traffic (general tensor data) and several sets of port tensors (for specific port numbers). It also includes the trained models for each type of tensor. The tensors extracted from network traffic in the period from July week 5 to the end of August can be used for evaluation. The naming convention is as follows:

Dataset Files

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[1] Mehdi Shajari, Hongxiang Geng, Kaixuan Hu, Alberto Leon-Garcia, "UGR'16 Tensor Time-Series Dataset", IEEE Dataport, 2022. [Online]. Available: http://dx.doi.org/10.21227/ma99-6j85. Accessed: Nov. 02, 2024.
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doi = {10.21227/ma99-6j85},
url = {http://dx.doi.org/10.21227/ma99-6j85},
author = {Mehdi Shajari; Hongxiang Geng; Kaixuan Hu; Alberto Leon-Garcia },
publisher = {IEEE Dataport},
title = {UGR'16 Tensor Time-Series Dataset},
year = {2022} }
TY - DATA
T1 - UGR'16 Tensor Time-Series Dataset
AU - Mehdi Shajari; Hongxiang Geng; Kaixuan Hu; Alberto Leon-Garcia
PY - 2022
PB - IEEE Dataport
UR - 10.21227/ma99-6j85
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Mehdi Shajari, Hongxiang Geng, Kaixuan Hu, Alberto Leon-Garcia. (2022). UGR'16 Tensor Time-Series Dataset. IEEE Dataport. http://dx.doi.org/10.21227/ma99-6j85
Mehdi Shajari, Hongxiang Geng, Kaixuan Hu, Alberto Leon-Garcia, 2022. UGR'16 Tensor Time-Series Dataset. Available at: http://dx.doi.org/10.21227/ma99-6j85.
Mehdi Shajari, Hongxiang Geng, Kaixuan Hu, Alberto Leon-Garcia. (2022). "UGR'16 Tensor Time-Series Dataset." Web.
1. Mehdi Shajari, Hongxiang Geng, Kaixuan Hu, Alberto Leon-Garcia. UGR'16 Tensor Time-Series Dataset [Internet]. IEEE Dataport; 2022. Available from : http://dx.doi.org/10.21227/ma99-6j85
Mehdi Shajari, Hongxiang Geng, Kaixuan Hu, Alberto Leon-Garcia. "UGR'16 Tensor Time-Series Dataset." doi: 10.21227/ma99-6j85