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Blockchain-Based Security System Applied to IoT Used in Intelligent Systems
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Blockchain-Based Security System Applied to IoT Used in Intelligent Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 2884

Special Issue Editors

Dr. Yongjun Ren

E-Mail Website
Guest Editor
School of Computer Science and Technology, Zhejiang Gongshang University, Hangzhou 310018, China
Interests: network security; applied cryptography
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Hu Xiong

E-Mail Website
Guest Editor
School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China
Interests: information security and cryptography
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of things (IoT), as a key technology bridging the real and digital worlds, is rapidly transforming our lives, work, and social interactions. Intelligent systems, such as smart homes, smart cities, smart healthcare, and industrial automation, rely on IoT technology to collect and process vast amounts of data, thereby enabling more efficient and smarter operations; however, with the exponential increase in the number of IoT devices and the expansion of their application areas, data security and privacy protection have become major challenges. In this context, blockchain technology, with its unique encryption, decentralization, and immutability, provides a new security solution for IoT-driven intelligent systems.

The application of the blockchain in intelligent systems, especially when integrated with the IoT, not only ensures data security and privacy but also enhances trust between devices and the transparency of the system. In smart city projects, the blockchain can be used to ensure the security of city operational data while also enhancing citizens' trust in intelligent services. In the field of smart manufacturing, the blockchain can realize supply chain transparency and the traceability of product quality. Additionally, the application of smart contracts can significantly improve the level of automation in IoT environments, such as automatically executing equipment maintenance and management tasks. Despite the numerous advantages that the blockchain brings to IoT smart systems, there are still a number of challenges that need to be addressed in applying it to IoT environments.

This Special Issue invites contributions on the following topics (but is not limited to them):

  • The scalability and performance optimization of blockchain technology, including cross-chain and off-chain channels, sharding, optimization consensus algorithms, etc.
  • The integration and innovation of blockchain technology with the Internet of things, metaverse, artificial intelligence, etc.
  • The application and challenges of blockchain and the Internet of things in green power systems, including green certification, green power traceability, and trading.
  • Application of the blockchain and Internet of things in the fields of intelligent medicine and sports health.
  • Integration and application of the blockchain in smart transportation Internet of things systems.
  • The challenges faced by intelligent supply chain management in the blockchain and Internet of things.
  • Application of the blockchain and Internet of things in smart city development.
  • Application of the blockchain in the industrial Internet of things.
  • Application of blockchain-based smart contracts in the Internet of things.
  • Application of the blockchain and Internet of things in energy smart management systems.

Dr. Yongjun Ren
Prof. Dr. Hu Xiong
Guest Editors

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. Sensors 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 2600 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
  • Internet of Things
  • smart contracts
  • data security
  • access control
  • intelligent systems
  • artificial intelligence

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Published Papers (3 papers)

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Research

20 pages, 630 KiB  
Article
Retrieval Integrity Verification and Multi-System Data Interoperability Mechanism of a Blockchain Oracle for Smart Healthcare with Internet of Things (IoT) Integration
by Ziyuan Zhou, Long Chen, Yekang Zhao, Xinyi Yang, Zhaoyang Han and Zheng He
Sensors 2024, 24(23), 7487; https://doi.org/10.3390/s24237487 - 24 Nov 2024
Viewed by 327
Abstract
The proliferation of Internet of Things (IoT) technology has significantly enhanced smart healthcare systems, enabling the collection and processing of vast healthcare datasets such as electronic medical records (EMRs) and remote health monitoring (RHM) data. However, this rapid expansion has also introduced critical [...] Read more.
The proliferation of Internet of Things (IoT) technology has significantly enhanced smart healthcare systems, enabling the collection and processing of vast healthcare datasets such as electronic medical records (EMRs) and remote health monitoring (RHM) data. However, this rapid expansion has also introduced critical challenges related to data security, privacy, and system reliability. To address these challenges, we propose a retrieval integrity verification and multi-system data interoperability mechanism for a Blockchain Oracle in smart healthcare with IoT Integration (RIVMD-BO). The mechanism uses the cuckoo filter technology to effectively reduce the computational complexity and ensures the authenticity and integrity of data transmission and use through data retrieval integrity verification. The experimental results and security analysis show that the proposed method can improve system performance while ensuring security. Full article
(This article belongs to the Special Issue Blockchain-Based Security System Applied to IoT Used in Intelligent Systems)
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17 pages, 5823 KiB  
Article
EADC: An Efficient Anonymous Data Collection Scheme with Blockchain in Internet of Things
by Zhiwei Si, Juhao Wang, Pengbiao Zhao, Xiaopei Wang and Jingcheng  Song
Sensors 2024, 24(22), 7162; https://doi.org/10.3390/s24227162 - 7 Nov 2024
Viewed by 441
Abstract
The integration of smart contracts (SCs) within blockchain technology represents a pivotal direction in the evolution of the Internet of Things (IoT), enabling decentralization and enhancing user trust in the system. However, ensuring data privacy is a fundamental challenge that must be addressed [...] Read more.
The integration of smart contracts (SCs) within blockchain technology represents a pivotal direction in the evolution of the Internet of Things (IoT), enabling decentralization and enhancing user trust in the system. However, ensuring data privacy is a fundamental challenge that must be addressed during the deployment of these SCs. Many scholars have adopted data aggregation to protect privacy, but these methods are difficult to achieve fine-grained data collection. To this end, this paper proposes an efficient anonymous data collection (EADC) scheme suitable for the IoT environment. The scheme combines matrix algorithms with homomorphic encryption (HE) technology to effectively cut off the connection between users and data during data upload. In addition, the EADC scheme introduces a sophisticated data grouping protocol to improve the overall efficiency of the system. Analysis shows that the scheme can achieve efficient data collection without compromising user privacy. Full article
(This article belongs to the Special Issue Blockchain-Based Security System Applied to IoT Used in Intelligent Systems)
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27 pages, 9078 KiB  
Article
An Efficient Privacy Protection Mechanism for Blockchain-Based Federated Learning System in UAV-MEC Networks
by Chaoyang Zhu, Xiao Zhu and Tuanfa Qin
Sensors 2024, 24(5), 1364; https://doi.org/10.3390/s24051364 - 20 Feb 2024
Cited by 2 | Viewed by 1446
Abstract
The widespread use of UAVs in smart cities for tasks like traffic monitoring and environmental data collection creates significant privacy and security concerns due to the transmission of sensitive data. Traditional UAV-MEC systems with centralized data processing expose this data to risks like [...] Read more.
The widespread use of UAVs in smart cities for tasks like traffic monitoring and environmental data collection creates significant privacy and security concerns due to the transmission of sensitive data. Traditional UAV-MEC systems with centralized data processing expose this data to risks like breaches and manipulation, potentially hindering the adoption of these valuable technologies. To address this critical challenge, we propose UBFL, a novel privacy-preserving federated learning mechanism that integrates blockchain technology for secure and efficient data sharing. Unlike traditional methods relying on differential privacy (DP), UBFL employs an adaptive nonlinear encryption function to safeguard the privacy of UAV model updates while maintaining data integrity and accuracy. This innovative approach enables rapid convergence, allowing the base station to efficiently identify and filter out severely compromised UAVs attempting to inject malicious data. Additionally, UBFL incorporates the Random Cut Forest (RCF) anomaly detection algorithm to actively identify and mitigate poisoning data attacks. Extensive comparative experiments on benchmark datasets CIFAR10 and Mnist demonstrably showcase UBFL’s effectiveness. Compared to DP-based methods, UBFL achieves accuracy (99.98%), precision (99.93%), recall (99.92%), and F-Score (99.92%) in privacy preservation while maintaining superior accuracy. Notably, under data pollution scenarios with varying attack sample rates (10%, 20%, and 30%), UBFL exhibits exceptional resilience, highlighting its robust capabilities in securing UAV gradients within MEC environments. Full article
(This article belongs to the Special Issue Blockchain-Based Security System Applied to IoT Used in Intelligent Systems)
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