Carol Lo Carol.Lo@uwe.ac.uk
TSU Business support coordinator NOM
Digital twins of cyber physical systems in smart manufacturing for threat simulation and detection with deep learning for time series classification
Lo, Carol; Win, Thu Yein; Rezaeifar, Zeinab; Khan, Zaheer; Legg, Phil
Authors
Thu Yein Win
Zeinab Rezaeifar
Zaheer Khan Zaheer2.Khan@uwe.ac.uk
Professor in Computer Science
Professor Phil Legg Phil.Legg@uwe.ac.uk
Professor in Cyber Security
Abstract
With increasing reliance on Cyber Physical Systems (CPS) for automation and control in Industry 4.0 and 5.0, ensuring their security against cyber threats has become paramount. Traditional security mechanisms, constrained by operational continuity and safety requirements, offer limited proactive threat detection capabilities against sophisticated Advanced Persistent Threats (APT). This research introduces the use of a Digital Twin testbed for repeatable simulation of diverse threat scenarios, generation of rich and varied datasets that depict a cyber incident, along with the ability to train time-series classification models for attack recognition. Our research aims to overcome the limitations of physical testbeds and challenges of data scarcity for Machine Learning (ML) or Deep Learning (DL) model development. By leveraging Digital Twins for data-driven analysis, this study proposes the use of supervised DL for accurate threat detection and classification in CPS within smart manufacturing. This paper demonstrates that Digital Twins testbed provides a cost-effective option for generating datasets to train and test supervised deep learning-based time series classification model for threat detection in CPS. It also discusses the benefits and limitations of the proposed testbed and suggests future research areas.
Presentation Conference Type | Conference Paper (unpublished) |
---|---|
Conference Name | The 29th International Conference on Automation and Computing (ICAC2024) |
Start Date | Aug 28, 2024 |
End Date | Aug 30, 2024 |
Deposit Date | Jun 12, 2024 |
Keywords | digital twin, testbed, cyber security, threat simulation and detection, cyber physical systems |
Public URL | https://uwe-repository.worktribe.com/output/12042560 |
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