Explainable AI-Driven Security Framework for Cyber-Physical Production Systems in Industry 4.0: Leveraging Immersive Embedded CIoT

This paper proposes a new security framework of Explainable Artificial Intelligence (XAI) for Cyber-Physical Production Systems (CPPSs) in the Industry 4.0 paradigm. An integral part of the framework is the incorporation of XAI into immersive embedded Consumer Internet of Things (CIoT) systems to promote transparency and interpretability, thereby improving real-time decision-making in AI-driven security mechanisms. The framework leverages SHAP and LIME techniques to provide human operators with clear insights into the AI-based security decision-making process, fostering trust and facilitating effective teaming between humans and AI assets. The proposed solution was validated and tested in an innovative manufacturing environment, where it could detect, interpret, and mitigate security threats in real-time, enhancing the security posture of the CPPS. Experimental results demonstrate that the framework achieves high accuracy in threat detection and significantly reduces false positives, as operators can fine-tune security policies based on the explainable AI insights. The importance of explainability in AI-driven security systems is emphasized, and it is demonstrated that immersive CIoT technologies can tackle the emerging security issues in CPPS.

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Publication Details

Journal
IEEE Transactions on Consumer Electronics
Published
2025-08-26
DOI
https://doi.org/10.1109/tce.2025.3602792
Primary Topic
Digital and Cyber Forensics
Type
article
Field-Weighted Citation Impact
0.00
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article

Explainable AI-Driven Security Framework for Cyber-Physical Production Systems in Industry 4.0: Leveraging Immersive Embedded CIoT

Thippa Reddy Gadekallu, Ahmad Almadhor, Muhammad Rehan Naeem, Muhammad Farhan et al.
IEEE Transactions on Consumer Electronics
Digital and Cyber Forensics
article

Explainable AI-Driven Security Framework for Cyber-Physical Production Systems in Industry 4.0: Leveraging Immersive Embedded CIoT

Thippa Reddy Gadekallu, Ahmad Almadhor, Muhammad Rehan Naeem, Muhammad Farhan, Ali Kashif Bashir, Zhu Zhu
article en

Abstract

This paper proposes a new security framework of Explainable Artificial Intelligence (XAI) for Cyber-Physical Production Systems (CPPSs) in the Industry 4.0 paradigm. An integral part of the framework is the incorporation of XAI into immersive embedded Consumer Internet of Things (CIoT) systems to promote transparency and interpretability, thereby improving real-time decision-making in AI-driven security mechanisms. The framework leverages SHAP and LIME techniques to provide human operators with clear insights into the AI-based security decision-making process, fostering trust and facilitating effective teaming between humans and AI assets. The proposed solution was validated and tested in an innovative manufacturing environment, where it could detect, interpret, and mitigate security threats in real-time, enhancing the security posture of the CPPS. Experimental results demonstrate that the framework achieves high accuracy in threat detection and significantly reduces false positives, as operators can fine-tune security policies based on the explainable AI insights. The importance of explainability in AI-driven security systems is emphasized, and it is demonstrated that immersive CIoT technologies can tackle the emerging security issues in CPPS.

IEEE Transactions on Consumer ElectronicsVol. 71(4)
Manchester Metropolitan University (GB), Zhejiang A & F University (CN), COMSATS University Islamabad (PK), University of Engineering and Technology Taxila (PK), Jouf University (SA), Jiaxing Vocational Technical College (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 67%
Digital and Cyber Forensics
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Explainable AI-Driven Security Framework for Cyber-Physical Production Systems in Industry 4.0: Leveraging Immersive Embedded CIoT — Thippa Reddy Gadekallu, Ahmad Almadhor, et al. · IEEE Transactions on Consumer Electronics (2025) | TGRS Research Map | TGRS