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Cited by 18Blockchain Technology Applications and SecurityAdvanced Authentication Protocols SecuritySmart Grid Security and Resilience

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Blockchain-Integrated Secure Authentication Framework for Smart Grid IoT Using Energy-Aware Consensus Mechanisms

Open access
Saleh, Omar Abdullah, Cevik, Mesut·2025·Sensors
DOI 10.3390/s25216622PMC PMC12609132
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Abstract

Integrating IoT devices into smart grids raises some hard problems related to safe data sharing, the ability to grow, and energy use. Blockchain provides a safe way to check identities without a central authority. Typical ways to confirm transactions, like Proof-of-Work (PoW), use a lot of power, making them bad for devices that cannot use much energy. This study introduces a safe authentication system using Blockchain, a Deep Neural Network (DNN), and a power-saving way to confirm transactions (EACM). The system picks validators based on how much power they have left and their trust scores to save power during confirmation. Using the IoT-Enabled Smart Grid Dataset, simulations showed a transaction speed of 372 TPS, which is 32% better than normal methods. The system correctly authenticates 98.69% of the time, with a confirmation delay of 5.9 milliseconds and an 18% drop in validator node energy use. Also, the system spots 98.4% of unauthorized access tries, with a false acceptance rate (FAR) of 1.7% and a false rejection rate (FRR) of 0.31%. These outcomes prove the system’s ability to offer safe, fast, and energy-saving authentication for big, real-time Smart Grid IoT setups.

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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 [24]

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Research works printed but not linked: 32

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Metadata

Authors
Saleh, O. A., & Cevik, M.
Affiliations
  • Altınbaş University (TR)
  • Department of Electrical and Computer Engineering, Altinbas University, 34217 Istanbul, Turkey
Corresponding author
Saleh, Omar Abdullah
ORCID
Cevik, Mesut
Venue
Sensors
Publisher
MDPI AG
Published
2025-10-28
Volume
25
Issue
21
Pages
6622
ISSN
1424-8220 (ISSN-L)
DOI
10.3390/s25216622
PMC
PMC12609132
OpenAlex
W4415650160
Cited by
18
References
2
Citations by year
2026: 16 · 2025: 2
FWCI
10.84
Type
journal article
Language
en
Open access
Licence
Locations
  • Sensors (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
  • Physical Sciences › Computer Science › Computer Networks and Communications › Advanced Authentication Protocols Security
  • Physical Sciences › Engineering › Control and Systems Engineering › Smart Grid Security and Resilience
Keywords
blockchain, smart grid, Internet of Things, authentication, validator selection, deep neural network, transaction confirmation, energy consumption, trust evaluation, unauthorized access detection, transaction throughput

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