A Framework for Runtime Safety of Industrial Control Systems Through Runtime Verification

Ensuring the safety of complex industrial control systems (ICS) cannot be fully achieved during the design and development phases. Many uncertainties and unknowns only become apparent during real-world operation, especially in the context of Industry 4.0, where ICS integrate increasing characteristics of cyber-physical systems (CPS), such as openness and connectivity. Runtime verification (RV) is extensively employed to guarantee the runtime safety of systems. However, current RV methods face substantial challenges in ICS, particularly due to extensive device heterogeneity, intricate real-time constraints, and the need for coordinating multiple controllers. In this article, we propose a novel framework that incorporates stream-based RV to ensure the runtime safety of ICS. By leveraging a communication bridge based on the open platform communications unified architecture (OPC UA) standard, our framework achieves platform compatibility. This framework, coupled with its nonintrusive verification feature, is well-suited for scenarios involving heterogeneous devices and collaborative controllers. Additionally, stream-based formal specification captures complex time-sensitive constraints, such as real-time synchronizations involving various signals, including triggering, duration, and timeout. To further enhance safety, the framework offers online correction strategies for addressing runtime violations, aiming to preserve or restore system safety. Experimental results from general case studies demonstrate that our approach surpasses existing methods in managing device heterogeneity, complex real-time constraints, and multicontroller cooperation scenarios.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-01-16
DOI
https://doi.org/10.1109/jiot.2025.3529887
Primary Topic
Safety Systems Engineering in Autonomy
Type
article
Field-Weighted Citation Impact
0.00

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article

A Framework for Runtime Safety of Industrial Control Systems Through Runtime Verification

Qin Li, Ting Wang, Yuanzhe Li, Tengfei Li et al.
IEEE Internet of Things Journal
Safety Systems Engineering in Autonomy
article

A Framework for Runtime Safety of Industrial Control Systems Through Runtime Verification

Qin Li, Ting Wang, Yuanzhe Li, Tengfei Li, Xia Mao
article en

Abstract

Ensuring the safety of complex industrial control systems (ICS) cannot be fully achieved during the design and development phases. Many uncertainties and unknowns only become apparent during real-world operation, especially in the context of Industry 4.0, where ICS integrate increasing characteristics of cyber-physical systems (CPS), such as openness and connectivity. Runtime verification (RV) is extensively employed to guarantee the runtime safety of systems. However, current RV methods face substantial challenges in ICS, particularly due to extensive device heterogeneity, intricate real-time constraints, and the need for coordinating multiple controllers. In this article, we propose a novel framework that incorporates stream-based RV to ensure the runtime safety of ICS. By leveraging a communication bridge based on the open platform communications unified architecture (OPC UA) standard, our framework achieves platform compatibility. This framework, coupled with its nonintrusive verification feature, is well-suited for scenarios involving heterogeneous devices and collaborative controllers. Additionally, stream-based formal specification captures complex time-sensitive constraints, such as real-time synchronizations involving various signals, including triggering, duration, and timeout. To further enhance safety, the framework offers online correction strategies for addressing runtime violations, aiming to preserve or restore system safety. Experimental results from general case studies demonstrate that our approach surpasses existing methods in managing device heterogeneity, complex real-time constraints, and multicontroller cooperation scenarios.

IEEE Internet of Things JournalVol. 12(11)
Huawei Technologies (China) (CN), Shanghai Urban Construction Design and Research Institute (Group) (CN), Shanghai Key Laboratory of Trustworthy Computing (CN), East China Normal University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 99%
Safety Systems Engineering in Autonomy
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