We elaborate on the dataset collected from our testbed developed at Washington University in St. Louis, to perform real-world IIoT operations, carrying out attacks that are more prelevant against IIoT systems. This dataset is to be utilized in the research of AI/ML based security solutions to tackle the intrusion problem.
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[1] Maede Zolanvari,
"WUSTL-IIOT-2021",
IEEE Dataport,
2021. [Online]. Available: http://dx.doi.org/10.21227/yftq-n229. Accessed: Feb. 07, 2025.
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url = {http://dx.doi.org/10.21227/yftq-n229},
author = {Maede Zolanvari },
publisher = {IEEE Dataport},
title = {WUSTL-IIOT-2021},
year = {2021} }
doi = {10.21227/yftq-n229},
url = {http://dx.doi.org/10.21227/yftq-n229},
author = {Maede Zolanvari },
publisher = {IEEE Dataport},
title = {WUSTL-IIOT-2021},
year = {2021} }
TY - DATA
T1 - WUSTL-IIOT-2021
AU - Maede Zolanvari
PY - 2021
PB - IEEE Dataport
UR - 10.21227/yftq-n229
ER -
T1 - WUSTL-IIOT-2021
AU - Maede Zolanvari
PY - 2021
PB - IEEE Dataport
UR - 10.21227/yftq-n229
ER -
Maede Zolanvari.
(2021).
WUSTL-IIOT-2021.
IEEE Dataport.
http://dx.doi.org/10.21227/yftq-n229
Maede Zolanvari,
2021.
WUSTL-IIOT-2021.
Available at:
http://dx.doi.org/10.21227/yftq-n229.
Maede Zolanvari.
(2021).
"WUSTL-IIOT-2021."
Web.
1. Maede Zolanvari.
WUSTL-IIOT-2021 [Internet].
IEEE Dataport; 2021.
Available from :
http://dx.doi.org/10.21227/yftq-n229
Maede Zolanvari.
"WUSTL-IIOT-2021."
doi:
10.21227/yftq-n229