Integration of Artificial Intelligence, Blockchain, and Quantum Cryptography for Securing the Industrial Internet of Things (IIoT): Recent Advancements and Future Trends

The swift growth of the Industrial Internet of Things (IIoT) offers tremendous potential to boost productivity, facilitate real-time decision-making, and automate procedures in various industries. However, as industries increasingly adopt IIoT, they face paramount data security, privacy, and system integrity challenges. Artificial intelligence (AI), Blockchain, and quantum cryptography are gaining significant attention as solutions to address these challenges. This paper comprehensively surveys advanced technologies and their potential applications for securing IIoT ecosystems. It reviews findings from 196 sources, including peer-reviewed journal articles, conference papers, books, book chapters, reports, and websites published between 2021 and 2025. The survey draws insights from leading platforms like Springer Nature, ACM Digital Library, Frontiers, Wiley Online Library, Taylor & Francis, IGI Global, Springer, ScienceDirect, MDPI, IEEE Xplore Digital Library, and Google Scholar. This paper explores AI-driven approaches to anomaly detection, predictive maintenance, and adaptive security mechanisms, demonstrating how machine learning (ML) and deep learning (DL) can identify and mitigate threats instantly. It also examines Blockchain technology, emphasizing its decentralized nature, immutability, and ability to secure data sharing and authentication within IIoT networks. The paper discusses quantum cryptography, which utilizes quantum mechanics for theoretically unbreakable encryption, ensuring secure communications in highly sensitive industrial environments. The integration of these technologies is analyzed to create a multi-layered defense against cyber threats, highlighting challenges in scalability, interoperability, and computational overhead. Finally, the paper reviews the current research, limitations and challenges, and future directions for securing IIoT with these advanced technologies. This survey offers valuable insights to researchers, engineers, and industry practitioners working to secure the expanding IIoT infrastructure.

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Publication Details

Journal
Applied Data Science and Analysis
Published
2025-03-27
DOI
https://doi.org/10.58496/adsa/2025/004
Citations
17
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
55.18
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article

Integration of Artificial Intelligence, Blockchain, and Quantum Cryptography for Securing the Industrial Internet of Things (IIoT): Recent Advancements and Future Trends

Guma Ali, Jenan Ayad, Ayodeji Olalekan Salau, Maad M. Mıjwıl et al.
17 citations
Applied Data Science and Analysis
Blockchain Technology Applications and Security
55.18
article

Integration of Artificial Intelligence, Blockchain, and Quantum Cryptography for Securing the Industrial Internet of Things (IIoT): Recent Advancements and Future Trends

Guma Ali, Jenan Ayad, Ayodeji Olalekan Salau, Maad M. Mıjwıl, Asiku Denis, Wamusi Robert, Klodian Dhoska, Malik Sallam, A. Jean Thomas, Aziku Samuel, Simon Peter Kabiito, Zaward Morish
article en
17 citations

Abstract

The swift growth of the Industrial Internet of Things (IIoT) offers tremendous potential to boost productivity, facilitate real-time decision-making, and automate procedures in various industries. However, as industries increasingly adopt IIoT, they face paramount data security, privacy, and system integrity challenges. Artificial intelligence (AI), Blockchain, and quantum cryptography are gaining significant attention as solutions to address these challenges. This paper comprehensively surveys advanced technologies and their potential applications for securing IIoT ecosystems. It reviews findings from 196 sources, including peer-reviewed journal articles, conference papers, books, book chapters, reports, and websites published between 2021 and 2025. The survey draws insights from leading platforms like Springer Nature, ACM Digital Library, Frontiers, Wiley Online Library, Taylor & Francis, IGI Global, Springer, ScienceDirect, MDPI, IEEE Xplore Digital Library, and Google Scholar. This paper explores AI-driven approaches to anomaly detection, predictive maintenance, and adaptive security mechanisms, demonstrating how machine learning (ML) and deep learning (DL) can identify and mitigate threats instantly. It also examines Blockchain technology, emphasizing its decentralized nature, immutability, and ability to secure data sharing and authentication within IIoT networks. The paper discusses quantum cryptography, which utilizes quantum mechanics for theoretically unbreakable encryption, ensuring secure communications in highly sensitive industrial environments. The integration of these technologies is analyzed to create a multi-layered defense against cyber threats, highlighting challenges in scalability, interoperability, and computational overhead. Finally, the paper reviews the current research, limitations and challenges, and future directions for securing IIoT with these advanced technologies. This survey offers valuable insights to researchers, engineers, and industry practitioners working to secure the expanding IIoT infrastructure.

Applied Data Science and AnalysisVol. 2025
University of Jordan (JO), University of Technology - Iraq (IQ), Polytechnic University of Tirana (AL), Afe Babalola University (NG), Iraqi University (IQ), Muni University (UG)
Openalex Percentile: Top 0%
Blockchain Technology Applications and Security
55.18
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