Blockchain-Enabled Secure Wireless Communication IoT Networks

Year : 2026 | Volume : 04 | Issue : 01 | Page : 10 14
    By

    Amit Dey,

  • Raushan Das,

  • Shiv Shankar Gond,

  • Gour Gopal Jana,

  • Niratyay Biswas,

  • Trilochan Patra,

  1. Student, Department of Electronics and Communication Engineering, Greater Kolkata College of Engineering and Management, South 24 Pargana, West Bengal, India
  2. Student, Department of Electronics and Communication Engineering, Greater Kolkata College of Engineering and Management, South 24 Pargana, West Bengal, India
  3. Student, Department of Electronics and Communication Engineering, Greater Kolkata College of Engineering and Management, South 24 Pargana, West Bengal, India
  4. Student, Department of Electronics and Communication Engineering, Greater Kolkata College of Engineering and Management, South 24 Pargana, West Bengal, India
  5. Student, Department of Electronics and Communication Engineering, Greater Kolkata College of Engineering and Management, South 24 Pargana, West Bengal, India
  6. Assistant Professor, Department of Electronics and Communication Engineering, Greater Kolkata College of Engineering and Management, South 24 Pargana, West Bengal, India

Abstract

Cloud-native environments with their distributed environments and transient workloads raise the intrinsic problem of traditional intrusion detection and response systems to unprecedented levels. Modern cloud platforms have rapid elasticity, microservice orientation, and dynamic scaling, which usually exceed the range of centralized security services, contributing to the problem of slower threat detection and a poor ability to contain the threat. The proliferation of the Internet of Things (IoT) gadgets across different sectors has led to significant safety and secrecy concerns in wireless communications. Centralized systems are susceptible to failures due to a single point of weakness and potential breaches. The specified method employs Ethereum-friendly smart contracts to serve as the decentralized arbitrators of the security occurrence and guarantee the security and non-repudiation of intrusion alerts reported by distributed monitoring units. When they are validated to be genuine, smart contracts automatically implement predetermined containment strategies that revolve around isolating malicious containers or withdrawing access rights, among others. The framework upholds the security policies that systematically and laxly establishes containment logic in immutable smart contracts to ensure that the security policies are enforced in real time. This paper presents a blockchain-enabled framework designed to ensure secure, decentralized, and tamper-resistant communication among IoT devices. The model uses smart contracts, lightweight consensus methods, and cryptographic hashing to provide authentication, integrity, and confidentiality. Performance tests using NS-3 and an Ethereum private test network show better resistance to attacks and efficient resource use.

Keywords: Blockchain framework, Ethereum, IoT, NS-3, wireless communication

[This article belongs to International Journal of Wireless Security and Networks ]

How to cite this article:
Amit Dey, Raushan Das, Shiv Shankar Gond, Gour Gopal Jana, Niratyay Biswas, Trilochan Patra. Blockchain-Enabled Secure Wireless Communication IoT Networks. International Journal of Wireless Security and Networks. 2026; 04(01):10-14.
How to cite this URL:
Amit Dey, Raushan Das, Shiv Shankar Gond, Gour Gopal Jana, Niratyay Biswas, Trilochan Patra. Blockchain-Enabled Secure Wireless Communication IoT Networks. International Journal of Wireless Security and Networks. 2026; 04(01):10-14. Available from: https://journals.stmjournals.com/ijwsn/article=2026/view=237513


References

  1. Alevizos L. Automated cybersecurity compliance and threat response using AI, blockchain and smart contracts. Int J Inf Technol. 2025;17:767–781. doi:10.1007/s41870-024-02324-9.
  2. Huang HJ, Otal HT, Canbaz MA. Federated learning in adversarial environments: Testbed design and poisoning resilience in cybersecurity. 2025 IEEE International Conference on Communications Workshops (ICC Workshops), Montreal, QC, Canada. 2025. p. 1079–1084. doi:10.1109/ICCWorkshops67674.2025.11162297.
  3. Joel MO, Chibunna UB, Daraojimba AI. Artificial intelligence, cyber security and blockchain for business intelligence. Int J Multidiscip Res Growth Eval. 2024;5:1383–1387. doi:10.54660/IJMRGE.2024.5.1.1383-1387.
  4. Manjappasetty Masagali BP, Nayak M. Empowering cloud-native security: The transformative role of artificial intelligence. SSRN Electron J. 2025;15. doi:10.2139/ssrn.5046089.
  5. Shashidhara R, Chirakarotu Nair R, Panakalapati PK. Promise of zero-knowledge proofs (ZKPs) for blockchain privacy and security: Opportunities, challenges, and future directions. Secur Priv. 2025;8:e461. doi:10.1002/spy2.461.
  6. Liu Z, Qian P, Wang X, Zhuang Y, Qiu L, Wang X. Combining graph neural networks with expert knowledge for smart contract vulnerability detection. IEEE Trans Knowl Data Eng. 2021;35:1–1. doi:10.1109/TKDE.2021.3095196.
  7. Zhang P, Wang Y, Kumar N, Jiang C, Shi G. A security- and privacy-preserving approach based on data disturbance for collaborative edge computing in social IoT systems. IEEE Trans Comput Soc Syst. 2022;9:97–108. doi:10.1109/TCSS.2021.3092746.
  8. Chen Q, Meng W, Han S, Li C, Chen HH. Reinforcement learning-based energy-efficient data access for airborne users in civil aircrafts-enabled SAGIN. IEEE Trans Green Commun Netw. 2021;5:934–949. doi:10.1109/TGCN.2021.3061631.
  9. Ethereum Network Statistics (2026). The Complete Guide to Ethereum. [Online] Ethereum. Available from: https://ethereum.org/
  10. ns-3 Consortium. ns-3.47. Version: 3.47 [online]. Network Simulator. 2026 Feb 16. Available from: https://www.nsnam.org/
Regular Issue Subscription Original Research
Volume 04
Issue 01
Received 14/10/2025
Accepted 30/12/2025
Published 24/02/2026
Publication Time 133 Days
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