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Applications of Blockchain and Artificial Intelligence Technology in Industry

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".

Deadline for manuscript submissions: 10 February 2026 | Viewed by 162

Special Issue Editor


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Guest Editor
School of Software Engineering, Sun Yat-sen University, Guangzhou 510275, China
Interests: distributed computing; federated computing; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The convergence of blockchain and artificial intelligence (AI) technologies is revolutionizing industrial processes, enabling secure, transparent, and intelligent systems. This Special Issue seeks high-quality research advancing the fundamental technologies of blockchain and artificial intelligence, as well as their integrated systems for industrial transformation. We encourage submissions that propose novel algorithms, optimize system architectures, or demonstrate measurable industrial impact. Both theoretical breakthroughs and applied innovations are welcome, with emphasis on reproducibility, scalability, and security.

We welcome contributions on, but not limited to, the following topics:

  1. Core Algorithm Innovations
  • New consensus mechanisms (e.g., AI-aided PoS/PoW variants);
  • Privacy-preserving AI/blockchain techniques (homomorphic encryption, zero-knowledge proofs);
  • On-chain machine learning algorithms;
  • Graph neural networks for blockchain analytics;
  • Optimization methods for decentralized AI training.
  1. System Architectures
  • Hybrid blockchain-AI system designs;
  • Sharding and layer-2 solutions for AI data pipelines;
  • Decentralized compute marketplaces;
  • Blockchain-based AI model provenance systems;
  • Trusted execution environments (TEEs) for hybrid systems.
  1. Enabling Technologies
  • AI-driven smart contract generation and verification;
  • Automated formal verification of blockchain–AI systems;
  • Oracles for real-world AI data feeds;
  • Tokenomics for decentralized AI ecosystems;
  • Quantum-resistant blockchain–AI hybrids.
  1. Industrial Applications (with technical depth)
  • Case studies requiring novel algorithmic solutions;
  • Performance benchmarks of deployed systems;
  • Interoperability frameworks across industries;
  • Regulatory-compliant architectures (GDPR, MiCA, etc.).

Dr. Jianguo Chen
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • blockchain
  • artificial intelligence
  • algorithms
  • optimize system architectures

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Published Papers (1 paper)

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Research

30 pages, 1282 KB  
Article
Enhancing IoT-LLN Security with IbiboRPLChain Solution: A Blockchain-Based Authentication Method
by Joshua T. Ibibo, Josiah E. Balota, Tariq Alwada’n and Olugbenga O. Akinade
Appl. Sci. 2025, 15(19), 10557; https://doi.org/10.3390/app151910557 - 29 Sep 2025
Abstract
The security of Internet of Things (IoT)–Low-Power and Lossy Networks (LLNs) is crucial for their widespread adoption in various applications. The standard routing protocol for IoT-LLNs, IPv6 Routing Protocol over Low-Power and Lossy Networks (RPL), is susceptible to insider attacks, such as the [...] Read more.
The security of Internet of Things (IoT)–Low-Power and Lossy Networks (LLNs) is crucial for their widespread adoption in various applications. The standard routing protocol for IoT-LLNs, IPv6 Routing Protocol over Low-Power and Lossy Networks (RPL), is susceptible to insider attacks, such as the version number attack (VNA), decreased rank attack (DRA), and increased rank attack (IRA). These attacks can significantly impact network performance and resource consumption. To address these security concerns, we propose the IbiboRPLChain Solution, a secure blockchain-based authentication method for RPL nodes. The proposed solution introduces an additional blockchain layer to the RPL architecture, enabling secure authentication of communication links between the routing layer and the sensor layer. The IbiboRPLChain Solution utilises smart contracts to trigger immediate authentication upon detecting routing attacks initiated by malicious nodes in an IoT-LLN environment. The evaluation of the proposed solution demonstrates its superior performance in mitigating insider attacks and enhancing IoT-LLN security compared to existing methods. The proposed solution effectively mitigates insider attacks by employing blockchain technology to authenticate communication links between routing and sensor nodes. This prevents malicious nodes from manipulating routing information and disrupting network operations. Additionally, the solution enhances IoT-LLN security by utilising smart contracts to trigger immediate authentication upon detecting suspicious activity, ensuring prompt action against potential threats. The findings of this research have significant implications for the development and deployment of secure IoT-LLNs. Full article
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