Flow-based intrusion detection algorithm for supervisory control and data acquisition systems: A real-time approach
Author | Teixeira, M. A. |
Author | Zolanvari, M. |
Author | Khan, K. M. |
Author | Jain, R. |
Author | Meskin, Nader |
Available date | 2022-04-14T08:45:36Z |
Publication Date | 2021 |
Publication Name | IET Cyber-Physical Systems: Theory and Applications |
Resource | Scopus |
Identifier | http://dx.doi.org/10.1049/cps2.12016 |
Abstract | Intrusion detection in supervisory control and data acquisition (SCADA) systems is integral because of the critical roles of these systems in industries. However, available approaches in the literature lack representative flow-based datasets and reliable real-time adaption and evaluation. A publicly available labelled dataset to support flow-based intrusion detection research specific to SCADA systems is presented. Cyberattacks were carried out against our SCADA system test bed to generate this flow-based dataset. Moreover, a flow-based intrusion detection system (IDS) is developed for SCADA systems using a deep learning algorithm. We used the dataset to develop this IDS model for real-time operations of SCADA systems to detect attacks momentarily after they happen. The results show empirical proof of the model’s adequacy when deployed online to detect cyberattacks in real time |
Sponsor | National Science Foundation; Washington University in St. Louis;?Qatar National Research Fund; Funda o de Amparo Pesquisa do Estado de So Paulo; Qatar University |
Language | en |
Publisher | John Wiley and Sons Inc |
Subject | Deep learning Intrusion detection Learning algorithms Network security SCADA systems Signal detection Statistical tests Cyber-attacks Flow based Intrusion detection algorithms Intrusion Detection Systems Real time Real-time operation Supervisory control and dataacquisition systems (SCADA) System test Real time systems |
Type | Article |
Pagination | 178-191 |
Issue Number | 3 |
Volume Number | 6 |
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Electrical Engineering [2579 items ]