Training and testing the accuracy of machine learning or deep learning based on cybersecurity applications requires gathering and analyzing various sources of data including the Internet of Things (IoT), especially Industrial IoT (IIoT). Minimizing high-dimensional spaces and choosing significant features and assessments from various data sources remain significant challenges in the investigation of those data sources. The research study introduces an innovative IIoT system dataset called UKMNCT_IIoT_FDIA, that gathered network, operating system, and telemetry data.

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[1] AKM Ahasan Habib, Mohammad Kamrul Hasan, "False Data Injection Attack Dataset for Industrial Internet of Things", IEEE Dataport, 2024. [Online]. Available: http://dx.doi.org/10.21227/k89d-5s27. Accessed: Jan. 21, 2025.
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doi = {10.21227/k89d-5s27},
url = {http://dx.doi.org/10.21227/k89d-5s27},
author = {AKM Ahasan Habib; Mohammad Kamrul Hasan },
publisher = {IEEE Dataport},
title = {False Data Injection Attack Dataset for Industrial Internet of Things},
year = {2024} }
TY - DATA
T1 - False Data Injection Attack Dataset for Industrial Internet of Things
AU - AKM Ahasan Habib; Mohammad Kamrul Hasan
PY - 2024
PB - IEEE Dataport
UR - 10.21227/k89d-5s27
ER -
AKM Ahasan Habib, Mohammad Kamrul Hasan. (2024). False Data Injection Attack Dataset for Industrial Internet of Things. IEEE Dataport. http://dx.doi.org/10.21227/k89d-5s27
AKM Ahasan Habib, Mohammad Kamrul Hasan, 2024. False Data Injection Attack Dataset for Industrial Internet of Things. Available at: http://dx.doi.org/10.21227/k89d-5s27.
AKM Ahasan Habib, Mohammad Kamrul Hasan. (2024). "False Data Injection Attack Dataset for Industrial Internet of Things." Web.
1. AKM Ahasan Habib, Mohammad Kamrul Hasan. False Data Injection Attack Dataset for Industrial Internet of Things [Internet]. IEEE Dataport; 2024. Available from : http://dx.doi.org/10.21227/k89d-5s27
AKM Ahasan Habib, Mohammad Kamrul Hasan. "False Data Injection Attack Dataset for Industrial Internet of Things." doi: 10.21227/k89d-5s27