Maede Zolanvari

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: May. 18, 2022.
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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
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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