ITM Web Conf.
Volume 56, 2023First International Conference on Data Science and Advanced Computing (ICDSAC 2023)
|Number of page(s)||7|
|Section||Networks & Information Security|
|Published online||09 August 2023|
Cyber-Attacks in IoT-enabled Cyber-physical Systems
Department of Information Science and Engineering, New Horizon College of Engineering, Bangalore, India
Cyber physical systems (CPS) that are Internet of Things (IoT) enabled might be difficult to secure since security measures designed for general data / value through the development (IT / OT) systems may not work as well in a CPS environment. Consequently, this research provides a two-level ensemble attack detection and attribution framework created for CPS, and more particularly in an industrial control system (ICS). For identifying assaults in unbalanced ICS environments, a decision tree integrated to an unique ensemble deep representation learning model is created at the first extent. An ensemble deep neural network is created for assault features at the second level. Applying actual data collections from the gas pipeline and water treatment system, Findings show that the suggested type is more effective than other competing methods with a similar level of computational complexity.
Key words: IOT / CPS / IT / OT / ICS / ML / DNN
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.