Transforming Industry 4.0 Security: Analysis of ABE and ABA Technologies

Jibran Saleem; Umar Raza; William Holderbaum

doi:10.62762/TIS.2024.993235

Article Information

Published in ICCK Transactions on Intelligent Systematics

Volume/Issue Volume 1, Issue 3, 2024

Pages 127-144

Cited by 6 (Crossref) 6 (Scopus)

Abstract

The increasing deployment of intelligent cyber-physical systems (CPS), autonomous devices, and IoT infrastructures in Industry 4.0 has introduced complex and dynamic security challenges that static, identity-based mechanisms are no longer sufficient to address. Intelligent industrial environments demand security frameworks capable of fine-grained, context-aware, and adaptive access control that can operate at scale across heterogeneous networked systems. In response to this need, Attribute-Based Encryption (ABE) and Attribute-Based Authentication (ABA) have emerged as essential building blocks for intelligent security architectures, enabling policy-driven data protection and authentication that are inherently aligned with the dynamic, attribute-rich nature of Industry 4.0 systems. This paper presents a structured review of ABE and ABA schemes, analysing key variants including KP-ABE, CP-ABE, and Decentralised ABE with respect to security, computational efficiency, and suitability for AI-augmented access control in Industry 4.0. Real-world deployments and future research directions, including AI-driven dynamic policy adaptation and energy-efficient schemes for intelligent edge devices, are also examined. The findings advance the understanding of ABE and ABA as core intelligent security control components, supporting the design of robust and autonomously adaptive security systems for next-generation industrial environments.

Graphical Abstract

Transforming Industry 4.0 Security: Analysis of ABE and ABA Technologies

Keywords

intelligent cyber-physical systems machine learning industry 4.0 cybersecurity cloud computing ABA ABE

Data Availability Statement

Not applicable.

Funding

This work was supported without any funding.

Conflicts of Interest

The authors declare no conflicts of interest.

Ethical Approval and Consent to Participate

Not applicable.

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APA Style

Saleem, J., Raza, U., & Holderbaum, W. (2024). Transforming Industry 4.0 Security: Analysis of ABE and ABA Technologies. ICCK Transactions on Intelligent Systematics, 1(3), 127-144. https://doi.org/10.62762/TIS.2024.993235

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TY  - JOUR
AU  - Saleem, Jibran
AU  - Raza, Umar
AU  - Holderbaum, William
PY  - 2024
DA  - 2024/10/21
TI  - Transforming Industry 4.0 Security: Analysis of ABE and ABA Technologies
JO  - ICCK Transactions on Intelligent Systematics
T2  - ICCK Transactions on Intelligent Systematics
JF  - ICCK Transactions on Intelligent Systematics
VL  - 1
IS  - 3
SP  - 127
EP  - 144
DO  - 10.62762/TIS.2024.993235
UR  - https://www.icck.org/article/abs/TIS.2024.993235
KW  - intelligent cyber-physical systems
KW  - machine learning
KW  - industry 4.0
KW  - cybersecurity
KW  - cloud computing
KW  - ABA
KW  - ABE
AB  - The increasing deployment of intelligent cyber-physical systems (CPS), autonomous devices, and IoT infrastructures in Industry 4.0 has introduced complex and dynamic security challenges that static, identity-based mechanisms are no longer sufficient to address. Intelligent industrial environments demand security frameworks capable of fine-grained, context-aware, and adaptive access control that can operate at scale across heterogeneous networked systems. In response to this need, Attribute-Based Encryption (ABE) and Attribute-Based Authentication (ABA) have emerged as essential building blocks for intelligent security architectures, enabling policy-driven data protection and authentication that are inherently aligned with the dynamic, attribute-rich nature of Industry 4.0 systems. This paper presents a structured review of ABE and ABA schemes, analysing key variants including KP-ABE, CP-ABE, and Decentralised ABE with respect to security, computational efficiency, and suitability for AI-augmented access control in Industry 4.0. Real-world deployments and future research directions, including AI-driven dynamic policy adaptation and energy-efficient schemes for intelligent edge devices, are also examined. The findings advance the understanding of ABE and ABA as core intelligent security control components, supporting the design of robust and autonomously adaptive security systems for next-generation industrial environments.
SN  - 3068-5079
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  -

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@article{Saleem2024Transformi,
  author = {Jibran Saleem and Umar Raza and William Holderbaum},
  title = {Transforming Industry 4.0 Security: Analysis of ABE and ABA Technologies},
  journal = {ICCK Transactions on Intelligent Systematics},
  year = {2024},
  volume = {1},
  number = {3},
  pages = {127-144},
  doi = {10.62762/TIS.2024.993235},
  url = {https://www.icck.org/article/abs/TIS.2024.993235},
  abstract = {The increasing deployment of intelligent cyber-physical systems (CPS), autonomous devices, and IoT infrastructures in Industry 4.0 has introduced complex and dynamic security challenges that static, identity-based mechanisms are no longer sufficient to address. Intelligent industrial environments demand security frameworks capable of fine-grained, context-aware, and adaptive access control that can operate at scale across heterogeneous networked systems. In response to this need, Attribute-Based Encryption (ABE) and Attribute-Based Authentication (ABA) have emerged as essential building blocks for intelligent security architectures, enabling policy-driven data protection and authentication that are inherently aligned with the dynamic, attribute-rich nature of Industry 4.0 systems. This paper presents a structured review of ABE and ABA schemes, analysing key variants including KP-ABE, CP-ABE, and Decentralised ABE with respect to security, computational efficiency, and suitability for AI-augmented access control in Industry 4.0. Real-world deployments and future research directions, including AI-driven dynamic policy adaptation and energy-efficient schemes for intelligent edge devices, are also examined. The findings advance the understanding of ABE and ABA as core intelligent security control components, supporting the design of robust and autonomously adaptive security systems for next-generation industrial environments.},
  keywords = {intelligent cyber-physical systems, machine learning, industry 4.0, cybersecurity, cloud computing, ABA, ABE},
  issn = {3068-5079},
  publisher = {Institute of Central Computation and Knowledge}
}

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