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Advanced Blockchain Technologies for Next-Generation Sensor Networks: Security, Privacy, and Scalability Solutions

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A Special Issue of Sensors (ISSN 1424-8220) belonging to the section "Sensor Networks".

Deadline for manuscript submissions: 30 January 2027 | Viewed by 4383

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Dr. Oleksandr Kuznetsov

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1. Department of Theoretical and Applied Sciences, eCampus University, Via Isimbardi 10, 22060 Novedrate, CO, Italy
2. Department of Political Sciences, Communication and International Relations, University of Macerata, Via Crescimbeni, 62100 Macerata, Italy
3. Department of Information and Communication Systems Security, V. N. Karazin Kharkiv National University, 4 Svobody Sq., 61022 Kharkiv, Ukraine
Interests: blockchain technology and decentralized systems; zero-knowledge proof technologies (zk-SNARKs, zk-STARKs); post-quantum cryptography and security protocols; IoT security and privacy-preserving technologies; biometric authentication and digital forensics; applied cryptography and information security; artificial intelligence in cybersecurity
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Special Issue Information

Dear Colleagues,

Background and History

The convergence of blockchain technology and sensor networks represents one of the most promising paradigms in modern distributed computing. As the Internet of Things (IoT) continues to expand exponentially, traditional centralized approaches to sensor data management face unprecedented challenges with regard to security, privacy, scalability, and trust. Blockchain technology offers revolutionary solutions by providing decentralized, tamper-proof, and transparent mechanisms for sensor data collection, verification, and storage.

Aim and Scope

This Special Issue aims to showcase cutting-edge research at the intersection of blockchain technology and sensor networks. We seek contributions that address fundamental challenges, including secure data aggregation, privacy-preserving analytics, lightweight consensus mechanisms for resource-constrained devices, zero-knowledge proof applications, and novel cryptographic protocols specifically designed for sensor network environments.

Cutting-edge Research Focus

We are particularly interested in innovative approaches leveraging advanced cryptographic techniques such as homomorphic encryption, zero-knowledge proofs (zk-SNARKs/zk-STARKs), post-quantum cryptography, and novel consensus mechanisms including DAG-based solutions. Research addressing real-world applications in smart cities, industrial IoT, healthcare monitoring, environmental sensing, and critical infrastructure protection is especially welcome.

Topics of Interest:

Novel blockchain architectures optimized for sensor networks.
Lightweight cryptographic protocols for resource-constrained IoT devices.
Privacy-preserving data aggregation and analytics solutions.
Zero-knowledge proof applications in sensor data verification.
Post-quantum security mechanisms for long-term sensor network protection.
Decentralized consensus protocols for large-scale sensor deployments.
Smart contracts for automated sensor network management.
Biometric authentication and digital identity solutions for sensor networks.
Performance evaluation and comparative studies of blockchain-enabled sensor systems.

Dr. Oleksandr Kuznetsov
Guest Editor

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Keywords

blockchain technology
sensor networks
IoT security
zero-knowledge proofs
post-quantum cryptography
decentralized consensus
privacy-preserving protocols
smart contracts
biometric authentication
distributed ledger technology

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Published Papers (4 papers)

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Research

35 pages, 1123 KB

Open AccessArticle

A Post-Quantum Sensor-to-Blockchain Transaction Framework with CRQC-Aware Exposure Minimization for Next-Generation Sensor Networks

by Bora Bugra Sezer

Sensors 2026, 26(14), 4327; https://doi.org/10.3390/s26144327 - 8 Jul 2026

Viewed by 429

Abstract

Blockchain-based sensor networks rely on public-key cryptography for transaction verification, auditability, and data integrity. However, widely used public-key mechanisms are quantum-vulnerable in the presence of Cryptographically Relevant Quantum Computers (CRQCs), requiring sensor-to-blockchain transactions to address both post-quantum security and exposure control. This paper proposes a post-quantum sensor-to-blockchain transaction framework that minimizes CRQC-aware exposure while preserving low-cost auditability. It defines a transaction workflow that represents sensor data through hash-based commitments instead of storing raw measurements on-chain. The workflow combines Module-Lattice-Based Digital Signature Algorithm (ML-DSA)-based authentication, threshold-based authorization, Module-Lattice-Based Key Encapsulation Mechanism (ML-KEM)-protected relay communication, and an event-based smart contract (EBSC) for compact audit recording. A Quantum Exposure Score (QES) is introduced as a transaction-level metric to quantify CRQC-induced exposure across cryptographic, relay, key-lifecycle, migration-readiness, and authorization dimensions. The framework is evaluated using differential pulse voltammetry (DPV) electrochemical sensor data, Constrained Application Protocol (CoAP) communication, and a Ganache-based blockchain, with scalability runs of up to 10,000 sensor transactions and ablation baselines. Compared with full on-chain storage, EBSC reduces gas consumption by approximately 80%, while QES decreases from 100 in the classical open scenario to 4 in the full framework. These results demonstrate that the proposed design provides a practical path for post-quantum secure sensor-to-blockchain transactions. Full article

(This article belongs to the Special Issue Advanced Blockchain Technologies for Next-Generation Sensor Networks: Security, Privacy, and Scalability Solutions)

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28 pages, 1458 KB

Open AccessArticle

A Method for Continuous Dual-Offline Payment of Cryptocurrency Based on Asset Credentials

by Huayou Si, Yaqian Huang, Guozheng Li, Yuanyuan Qi, Wei Chen and Zhigang Gao

Sensors 2026, 26(10), 3039; https://doi.org/10.3390/s26103039 - 12 May 2026

Cited by 1 | Viewed by 1288

Abstract

With the widespread adoption of cryptocurrencies, the ability to conduct continuous offline payments has increasingly become a critical technological requirement. In network-constrained scenarios, current dual-offline payment technologies are useful for single transactions. However, their limitations in continuous payment scenarios have become increasingly evident, making them unable to meet real-world application needs. This has prompted the industry to demand more urgent innovations in research on continuous offline payment capabilities. To address these challenges, this paper proposes a continuous dual-offline payment system capable of supporting multiple continuous payments. The system integrates elliptic curve cryptography (ECC) and zero-knowledge proof (ZKP) technology to generate secure asset credentials, ensuring both immutability and privacy credentials throughout the offline payment lifecycle. A dynamic credential decomposition mechanism enables the splitting of input credentials into change credentials and receipt credentials, facilitating uninterrupted dual-offline payments between hardware wallets. Additionally, it incorporates a batch verification scheme based on smart contracts, utilizing zero-balance verification and chained hash tracing to ensure payment uniqueness and prevent double-spending attacks, thereby guaranteeing the verifiability and validity of payment settlements. Experimental evaluations demonstrate that the proposed system reduces gas consumption per payment and improves execution efficiency during batch processing, combining high security with strong performance. This research provides a feasible solution for the application of digital currencies in offline scenarios, carrying significant theoretical value and practical significance for driving technological innovation and application expansion in the cryptocurrency field. In addition to cryptocurrency payments, the proposed system is also applicable to IoT and sensor network environments. Many IoT devices operate in disconnected or network-limited areas and require secure micro-transactions. Our dual-offline payment mechanism supports such scenarios, as the main cryptographic operations are lightweight enough for typical IoT hardware. This further extends the practical value of our system beyond traditional cryptocurrency payments. Full article

(This article belongs to the Special Issue Advanced Blockchain Technologies for Next-Generation Sensor Networks: Security, Privacy, and Scalability Solutions)

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22 pages, 6452 KB

Open AccessArticle

Blockchain-Enabled Uncertainty-Aware Passive Wi-Fi Localization for Secure Critical Infrastructure Sensor Networks

by Dmytro Prokopovych-Tkachenko, Oleksandr Galushchenko, Olga Torstensson, Volodymyr Zvieriev, Saltanat Adilzhanova and Edison Pignaton de Freitas

Sensors 2026, 26(9), 2797; https://doi.org/10.3390/s26092797 - 30 Apr 2026

Cited by 1 | Viewed by 800

Abstract

Passive Wi-Fi localization for critical-infrastructure security operations centers (SOCs) faces three interconnected limitations. First, many existing methods produce single-point coordinate estimates without calibrated uncertainty, making them unsuitable for automated SOC response. Second, localization pipelines often lack an evidentiary chain of custody, limiting reliable post-incident auditability. Third, SOC automation cannot safely rely on uncalibrated confidence values because erroneous high-impact actions and missed escalations carry asymmetric operational costs. This study presents a Blockchain-Enabled Uncertainty-Aware Passive Wi-Fi Localization framework for heterogeneous sensor networks composed of stationary sensors, mobile receivers, and UAV-assisted collection nodes. Instead of producing a single coordinate estimate, the method derives a posterior spatial distribution with calibrated uncertainty from monitor-mode observations, including RSSI aggregates, management/control frame features, channel occupancy indicators, and receiver logs. The framework combines three tightly coupled components: (i) Bayesian coordinate estimation with robust loss functions and range-dependent error modeling; (ii) uncertainty calibration that converts posterior confidence into operational SOC response modes (AUTO, VERIFY, and OBSERVE) via empirical coverage metrics and reliability diagrams; and (iii) a permissioned evidentiary logging layer that anchors integrity-relevant metadata and policy labels on-chain while keeping raw telemetry off-chain for tamper-evident auditability and scalability. The coupling between layers is explicit: calibrated confidence scores govern smart-contract gating conditions, and smart-contract policy thresholds feed back into the calibration stage. Field validation shows that localization performance degrades markedly beyond approximately 40 m, indicating a practical boundary for confident automated action. The proposed framework integrates passive sensing, uncertainty-aware localization, and blockchain-based evidentiary trust for secure critical-infrastructure sensor networks. Its key contributions are: (1) a posterior-distribution-based passive localization pipeline; (2) empirical coverage metrics for calibrating SOC response thresholds; (3) a hybrid on-chain/off-chain architecture linking localization outputs to a permissioned ledger; and (4) field validation establishing the 40 m operational validity boundary. Full article

(This article belongs to the Special Issue Advanced Blockchain Technologies for Next-Generation Sensor Networks: Security, Privacy, and Scalability Solutions)

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21 pages, 790 KB

Open AccessArticle

Performance Evaluation of zk-SNARK Protocols for Privacy-Preserving Sensor Data Verification: A Systematic Benchmarking Study

by Oleksandr Kuznetsov, Yelyzaveta Kuznetsova, Gulzat Ziyatbekova, Yuliia Kovalenko and Rostyslav Palahusynets

Sensors 2026, 26(8), 2486; https://doi.org/10.3390/s26082486 - 17 Apr 2026

Cited by 1 | Viewed by 1119

Abstract

The proliferation of sensor networks in critical infrastructure, healthcare monitoring, and smart city applications demands robust privacy-preserving mechanisms for data verification. Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) offer a promising cryptographic primitive that enables data integrity verification without revealing sensitive sensor readings. However, the practical feasibility of deploying zk-SNARKs in resource-constrained sensor network environments remains insufficiently characterized. This paper presents a systematic benchmarking study of the Groth16 zk-SNARK protocol across eight representative circuit types spanning six orders of magnitude in computational complexity, from basic arithmetic operations (1 constraint) to ECDSA signature verification (1,510,185 constraints). Using an automated open-source benchmarking framework built on the Circom-snarkjs toolchain, we conducted 160 statistically controlled measurements (20 iterations per circuit) with cold/warm separation, collecting proof generation time, verification time, proof size, memory consumption, and witness generation overhead. Our results demonstrate that Groth16 proofs maintain a constant size of

804.7 \pm 1.7

bytes and near-constant verification time of

0.662 \pm 0.032

s regardless of circuit complexity, with coefficients of variation below 5% across all circuit types. Proof generation time exhibits sub-linear scaling (

α = 0.256

R^{2} = 0.608

), with statistically significant differences between circuit categories confirmed by one-way ANOVA (

F = 355.0

p < 10^{- 79}

η^{2} = 0.94

). We identify three operational deployment tiers for sensor network architectures and estimate energy budgets for battery-powered devices. These findings provide actionable guidance for the design of privacy-preserving data verification systems in next-generation sensor networks. Full article

(This article belongs to the Special Issue Advanced Blockchain Technologies for Next-Generation Sensor Networks: Security, Privacy, and Scalability Solutions)

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