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Cited by 10Blockchain Technology Applications and SecurityBlockchain Technology in Education and LearningInternet of Things and AI

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Securing IoT Sensors Using Sharding-Based Blockchain Network Technology Integration: A Systematic Review

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Aslam, Ammad, Postolache, Octavian, Oliveira, Sancho, Pereira, José Dias·2025·Sensors
DOI 10.3390/s25030807PMC PMC11820452
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Abstract

Sharding is an emerging blockchain technology that is used extensively in several fields such as finance, reputation systems, the IoT, and others because of its ability to secure and increase the number of transactions every second. In sharding-based technology, the blockchain is divided into several sub-chains, also known as shards, that enhance the network throughput. This paper aims to examine the impact of integrating sharding-based blockchain network technology in securing IoT sensors, which is further used for environmental monitoring. In this paper, the idea of integrating sharding-based blockchain technology is proposed, along with its advantages and disadvantages, by conducting a systematic literature review of studies based on sharding-based blockchain technology in recent years. Based on the research findings, sharding-based technology is beneficial in securing IoT systems by improving security, access, and transaction rates. The findings also suggest several issues, such as cross-shard transactions, synchronization issues, and the concentration of stakes. With an increased focus on showcasing the important trade-offs, this paper also offers several recommendations for further research on the implementation of blockchain network technology for securing IoT sensors with applications in environment monitoring. These valuable insights are further effective in facilitating informed decisions while integrating sharding-based technology in developing more secure and efficient decentralized networks for internet data centers (IDCs), and monitoring the environment by picking out key points of the data.

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  • Studies published in Sensors have shown that anomaly detection, blockchain-based integrity verification, and AI-driven analytics enhance trust in industrial sensor networks.

    “Studies published in Sensors (e.g., [19,22,23,24]) have shown that anomaly detection, blockchain-based integrity verification, and AI-driven analytics enhance trust in industrial sensor networks.”

    From Sensor-Based Cyber Risk Management in Railway Infrastructure Under the NIS2 Directive (2025) · cites this paper as [23]

    The Introduction describes blockchain records as tamper-resistant and protective of transaction integrity. Section 3.1 discusses anomaly detection in IoT systems and the potential of AI and blockchain for intrusion-detection systems. The paper does not establish that all three approaches enhance trust specifically in industrial sensor networks; its discussion of trustworthiness in Section 4.2 concerns blockchain-based IoT sensor security. (LLM, conf=0.84)

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Metadata

Authors
Aslam, A., Postolache, O., Oliveira, S., & Pereira, J. D.
Affiliations
  • Iscte – Instituto Universitário de Lisboa (PT)
  • Instituto de Telecomunicações, Av. Rovisco Pais, 1049-001 Lisbon, Portugal
ORCID
Venue
Sensors
Publisher
MDPI AG
Published
2025-01-29
Volume
25
Issue
3
Pages
807
ISSN
1424-8220 (ISSN-L)
DOI
10.3390/s25030807
PMC
PMC11820452
OpenAlex
W4406929411
Cited by
10
References
1
Citations by year
2026: 5 · 2025: 5
FWCI
1.64
Type
journal article
Language
en
Open access
Licence
Locations
  • Sensors (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Repositório do ISCTE-IUL (submittedVersion, other-oa)
Funders
FCT/MECI through national funds and co-funded EU funds (UID/50008)
Topics
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
  • Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
Keywords
sharding, blockchain, Internet of Things security, IoT sensors, environmental monitoring, cross-shard transactions, decentralized networks, internet data centers

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