Enhancing Security in Industry 4.0 / 5.0 Data Sharing: A Risk Modeling Approach

Alexandros Nizamis; Nadia Masood Khan; Usman Wajid; Stefano Modafferi; Nikolay Mehandjiev; Konstantinos Votis

doi:10.1109/DCOSS-IoT65416.2025.00076

Enhancing Security in Industry 4.0 / 5.0 Data Sharing: A Risk Modeling Approach

Alexandros Nizamis, Nadia Masood Khan, Usman Wajid, Stefano Modafferi, Nikolay Mehandjiev, Konstantinos Votis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Today, the advancement of Industries 4.0 and 5.0 has enabled the digital transformation of the manufacturing domain and the creation of data-sharing ecosystems. A cornerstone of this advancement is the Internet of Things, which has enabled the realization of applications related to real-time monitoring, automation, and analytics. However, IoT-enabled data sharing scenarios across organizations have also introduced significant security, privacy, and trust challenges. This paper presents the Security Risk Modeler (SRM), a tool designed to address these challenges by providing a systematic approach to identifying, analyzing, and mitigating security risks in Industry 4.0/5.0 data sharing environments. The tool is applied to a real-world industrial waste management scenario that involves IoT enabled waste bins, cloud-based analytics, and data sharing between two companies. Through this case study, SRM demonstrates its ability to model complex systems, identify threats, and propose actionable mitigation controls. Evaluations by industry stakeholders highlighted the tool's usability, risk analysis capabilities, and potential for broader adoption in securing Industry 4.0/5.0 ecosystems.

Original language	English
Title of host publication	2025 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT)
Publisher	IEEE
Pages	443-450
Number of pages	8
ISBN (Electronic)	9798331543723
ISBN (Print)	9798331543730 (PoD)
DOIs	https://doi.org/10.1109/DCOSS-IoT65416.2025.00076
Publication status	Published - 5 Aug 2025
Event	21st Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2025 - Lucca, Italy Duration: 9 Jun 2025 → 11 Jun 2025

Publication series

Name	International Conference on Distributed Computing in Sensor Systems and workshops
Publisher	IEEE
ISSN (Print)	2325-2936
ISSN (Electronic)	2325-2944

Conference

Conference	21st Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2025
Country/Territory	Italy
City	Lucca
Period	9/06/25 → 11/06/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Keywords

cybersecurity
data sharing
Industry 4.0 and 5.0
risk modeling
threat mitigation

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Hardware and Architecture
Information Systems
Information Systems and Management
Control and Optimization

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/DCOSS-IoT65416.2025.00076

Cite this

Nizamis, A., Khan, N. M., Wajid, U., Modafferi, S., Mehandjiev, N., & Votis, K. (2025). Enhancing Security in Industry 4.0 / 5.0 Data Sharing: A Risk Modeling Approach. In 2025 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) (pp. 443-450). (International Conference on Distributed Computing in Sensor Systems and workshops). IEEE. https://doi.org/10.1109/DCOSS-IoT65416.2025.00076

Nizamis, Alexandros ; Khan, Nadia Masood ; Wajid, Usman et al. / Enhancing Security in Industry 4.0 / 5.0 Data Sharing : A Risk Modeling Approach. 2025 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). IEEE, 2025. pp. 443-450 (International Conference on Distributed Computing in Sensor Systems and workshops).

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abstract = "Today, the advancement of Industries 4.0 and 5.0 has enabled the digital transformation of the manufacturing domain and the creation of data-sharing ecosystems. A cornerstone of this advancement is the Internet of Things, which has enabled the realization of applications related to real-time monitoring, automation, and analytics. However, IoT-enabled data sharing scenarios across organizations have also introduced significant security, privacy, and trust challenges. This paper presents the Security Risk Modeler (SRM), a tool designed to address these challenges by providing a systematic approach to identifying, analyzing, and mitigating security risks in Industry 4.0/5.0 data sharing environments. The tool is applied to a real-world industrial waste management scenario that involves IoT enabled waste bins, cloud-based analytics, and data sharing between two companies. Through this case study, SRM demonstrates its ability to model complex systems, identify threats, and propose actionable mitigation controls. Evaluations by industry stakeholders highlighted the tool's usability, risk analysis capabilities, and potential for broader adoption in securing Industry 4.0/5.0 ecosystems.",

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Nizamis, A, Khan, NM, Wajid, U, Modafferi, S, Mehandjiev, N & Votis, K 2025, Enhancing Security in Industry 4.0 / 5.0 Data Sharing: A Risk Modeling Approach. in 2025 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). International Conference on Distributed Computing in Sensor Systems and workshops, IEEE, pp. 443-450, 21st Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2025, Lucca, Italy, 9/06/25. https://doi.org/10.1109/DCOSS-IoT65416.2025.00076

Enhancing Security in Industry 4.0 / 5.0 Data Sharing: A Risk Modeling Approach. / Nizamis, Alexandros; Khan, Nadia Masood; Wajid, Usman et al.
2025 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). IEEE, 2025. p. 443-450 (International Conference on Distributed Computing in Sensor Systems and workshops).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Mehandjiev, Nikolay

AU - Votis, Konstantinos

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N2 - Today, the advancement of Industries 4.0 and 5.0 has enabled the digital transformation of the manufacturing domain and the creation of data-sharing ecosystems. A cornerstone of this advancement is the Internet of Things, which has enabled the realization of applications related to real-time monitoring, automation, and analytics. However, IoT-enabled data sharing scenarios across organizations have also introduced significant security, privacy, and trust challenges. This paper presents the Security Risk Modeler (SRM), a tool designed to address these challenges by providing a systematic approach to identifying, analyzing, and mitigating security risks in Industry 4.0/5.0 data sharing environments. The tool is applied to a real-world industrial waste management scenario that involves IoT enabled waste bins, cloud-based analytics, and data sharing between two companies. Through this case study, SRM demonstrates its ability to model complex systems, identify threats, and propose actionable mitigation controls. Evaluations by industry stakeholders highlighted the tool's usability, risk analysis capabilities, and potential for broader adoption in securing Industry 4.0/5.0 ecosystems.

AB - Today, the advancement of Industries 4.0 and 5.0 has enabled the digital transformation of the manufacturing domain and the creation of data-sharing ecosystems. A cornerstone of this advancement is the Internet of Things, which has enabled the realization of applications related to real-time monitoring, automation, and analytics. However, IoT-enabled data sharing scenarios across organizations have also introduced significant security, privacy, and trust challenges. This paper presents the Security Risk Modeler (SRM), a tool designed to address these challenges by providing a systematic approach to identifying, analyzing, and mitigating security risks in Industry 4.0/5.0 data sharing environments. The tool is applied to a real-world industrial waste management scenario that involves IoT enabled waste bins, cloud-based analytics, and data sharing between two companies. Through this case study, SRM demonstrates its ability to model complex systems, identify threats, and propose actionable mitigation controls. Evaluations by industry stakeholders highlighted the tool's usability, risk analysis capabilities, and potential for broader adoption in securing Industry 4.0/5.0 ecosystems.

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Nizamis A, Khan NM, Wajid U, Modafferi S, Mehandjiev N, Votis K. Enhancing Security in Industry 4.0 / 5.0 Data Sharing: A Risk Modeling Approach. In 2025 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). IEEE. 2025. p. 443-450. (International Conference on Distributed Computing in Sensor Systems and workshops). doi: 10.1109/DCOSS-IoT65416.2025.00076

Enhancing Security in Industry 4.0 / 5.0 Data Sharing: A Risk Modeling Approach

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Fingerprint

Cite this