Open Access

ARTICLE

Lightweight Blockchain-Edge Security Framework for IoT Smart Spaces: Architecture, Threat Mitigation, and Real-World Validation

Martin Parmar¹, Het Khatusuriya¹, Dharmendra Chauhan², Mrugendra Rahevar¹, Bimal Patel³, Agbotiname Lucky Imoize⁴, Chun-Ta Li^5,*, Hiren Mewada⁶

1 Department of Computer Engineering, Chandubhai S. Patel Institute of Technology, Charotar University of Science and Technology, Anand, Gujarat, India
2 Department of Electronics and Communication Engineering, Chandubhai S. Patel Institute of Technology, Charotar University of Science and Technology, Anand, Gujarat, India
3 Department of Information Technology, Chandubhai S. Patel Institute of Technology, Charotar University of Science and Technology, Anand, Gujarat, India
4 Department of Electrical and Electronics Engineering, Faculty of Engineering, University of Lagos, Akoka, Lagos, Nigeria
5 Bachelor’s Program of Artificial Intelligence and Information Security, Fu Jen Catholic University, New Taipei City, Taiwan
6 Electrical Engineering Department, Prince Mohammad Bin Fahd University, Al Khobar, Saudi Arabia

* Corresponding Author: Chun-Ta Li. Email:

Computer Modeling in Engineering & Sciences 2026, 148(3), 49 https://doi.org/10.32604/cmes.2026.087402

Received 16 June 2026; Accepted 24 August 2026; Issue published 28 September 2026

Abstract

The rapid growth of Internet of Things (IoT) devices in smart urban areas—health monitoring, urban infrastructure, environmental sensing, and energy management—creates attack surfaces that centralized security architectures cannot adequately safeguard. Traditional approaches impose inadequate latency, introduce a single point of failure, and scale poorly to the distributed, resource-constrained nature of IoT ecosystems. This work proposes a formally modeled, hardware-validated four-tier blockchain-edge security framework that integrates a permissioned Hyperledger Fabric network (Raft ordering), tiered AES-128/256 cryptography, and IoT-specific smart contracts implementing Decentralized Identifier (DID) and OAuth2-based access control. Experimental evaluation on Raspberry Pi 4 and NVIDIA Jetson Orin edge hardware, with baselines re-implemented on the identical testbed where feasible, confirms: 500 ± 23 transactions per second (TPS) throughput—150% above AEchain’s reported figure and 594% above private Ethereum PoA—with 110 ± 18 ms end-to-end latency (P99 = 167 ms, satisfying the 200 ms industrial real-time threshold), 86.6% latency reduction vs. cloud-only baselines, 15%–20% cryptographic overhead reduction via tiered AES strategy, and 98.6% on-chain storage reduction through hash-only ledger commits. A formal Dolev-Yao adversary model with a 15-vector CIA threat taxonomy and complete design-to-evidence traceability distinguishes this work from prior simulation-based approaches.

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Keywords

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