Serial Number: 98
Year: 2021
Kind of Traffic: Real
Publicly Available: Yes
Count of Records: 2.7GB
Features Count: 23
No. of citations: 88
Attack Type: injection, reconnaissance, DoS.
Download Links: https://www.cse.wustl.edu/~jain/iiot2/index.html
Abstract: Zolanvari and colleagues identified the absence of datasets specifically designed for Industrial Internet of Things network security. To address this deficiency, they suggested a compact test environment created to mimic a standard Industrial Control System (ICS), focusing on a water level monitoring system in particular. The experimental setup includes a Programmable Logic Controller (PLC), four actuators, three sensors, and four additional versatile devices, with one of them operating as the attacker. Using the Modbus protocol, communication between actuators and sensors was enabled. The researchers equipped the testbed with measuring instruments and monitored the networks activity under normal conditions and during a simulated attack, capturing data over a period of 53 hours. To model potential attack scenarios, four categories of attacks were executed: reconnaissance, command injection, Denial of Service (DoS), and the installation of a backdoor. A portion of their recorded data was released to the public as the Dataset WUSTL-IIOT-2021, presented in a CSV format. There are 41 features and one feature is assigned as attack label. These characteristics offer a synopsis of the network traffic documented within the testbed. Researchers in their study, focusing on the application of Explainable Artificial Intelligence (AI) to enhance the security of the Industrial Internet of Things (IIoT), utilize this dataset.