Smart Chain: AI-Driven Blockchain Framework for IoT Security

IPEM Journal Computer Applications > Smart Chain: AI-Driven Blockchain Framework for IoT Security

Smart Chain: AI-Driven Blockchain Framework for IoT Security

Mohd Mursaleem Khan, Mukhtar Ali

Vol 10 , Issue 1 , December 2025 | Pages: 122-133

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Published Online: December, 2025

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Author Details

1. Mohd Mursaleem Khan, Research scholar, Vishveshwarya Group of Institutions, Dadri, Ghaziabad, India
2. Mukhtar Ali, Vishveshwarya Group of Institutions, Dadri, Ghaziabad, India

The rapid expansion of IoT systems significantly scales up the number, heterogeneity, and vulnerability of connected devices, making the IoT ecosystem an attractive target for cyberattacks. Traditional security mechanisms based on a centralized authority fail to provide scalability, transparency, and real-time threat mitigation in such dynamic environments. Although blockchain technology offers decentralisation, immutability, and trust, its direct adaptation is not feasible in IoT systems due to the significant computational overhead and resource constraints. Similarly, AI enables intelligent threat detection but lacks secure data integrity and trustworthy coordination in a standalone deployment. This paper proposes the Smart Chain AI-driven blockchain framework to enhance IoT security in a scalable and resource-efficient manner. Smart Chain integrates lightweight blockchain mechanisms with AI-based intelligence to offer secure device authentication, dynamic access control, adaptive consensus, and real-time anomaly detection. The proposed AI-driven blockchain framework leverages AI to analyze IoT behavioural patterns, optimize consensus selection, and automate security responses using smart contracts, while blockchain ensures data integrity, transparency, and tamper-resistant logging. Unlike existing solutions that tend to consider AI and blockchain as two orthogonal components, Smart Chain presents a unified architecture tailored for resource-constrained IoT environments. In this regard, the proposed framework can improve security, trust management, and system resilience with minimal computational and energy overhead. Smart Chain demonstrates that the synergistic integration of AI with blockchain can help overcome current limitations in IoT security, therefore providing a practical and extensible solution for next-generation secure IoT ecosystems.

Keywords

Internet of Things (IoT), Blockchain Technology, Artificial Intelligence, IoT Security, Smart Contracts, Lightweight Consensus, Anomaly Detection, Decentralized Systems, Trust Management.

  • Xu et al., “Consensus Mechanism of IoT Based on Blockchain,” IEEE Access, vol. 8, pp. 12345–12356, 2020.
  • Novo, “Blockchain-Based Access Control for the Internet of Things: A Survey,” Computer Networks, vol. 192, p. 108040, 2021.
  • Dorri, S. S. Kanhere, and R. Jurdak, “Blockchain-Based Access Control Scheme for IoT,” Sensors, vol. 22, no. 5, p. 1896, 2022.
  • A. Ferrag and L. Shu, “Blockchain Technology-Based Solutions for IoT Security,” Journal of King Saud University – Computer and Information Sciences, vol. 34, no. 8, pp. 4764–4776, 2022.
  • Alasmaryet al., “Intrusion Detection in IoT using Machine Learning and Blockchain,” IEEE Internet of Things Journal, vol. 10, no. 4, pp. 3210–3222, 2023.
  • Islam, M. U. Mahmud, and A. Jolfaei, “A Lightweight Security Framework using Blockchain and Machine Learning,” Future Generation Computer Systems, vol. 139, pp. 82–94, 2023.
  • Chen et al., “AI-Driven Blockchain Framework for Secure IoT Data Analysis,” Electronics, vol. 13, no. 4, p. 812, 2024.
  • Alladi, V. Chamola, and N. Guizani, “Blockchain Technology for IoT Security and Trust: A Review,” Future Internet, vol. 16, no. 2, p. 45, 2024.
  • Xu et al., “Resource-Efficient Consensus Mechanism for IoT Devices,” IEEE Transactions on Green Communications and Networking, vol. 8, no. 1, pp. 210–222, 2024.
  • K. Sharma and J. H. Park, “Smart Contract-Based Blockchain Solution for IoT Networks,” Future Generation Computer Systems, vol. 152, pp. 455–468, 2024.
  • K. Das et al., “AI-Integrated Trust Management and Blockchain for Industrial IoT,” Expert Systems with Applications, vol. 237, p. 121234, 2025.
  • Zhang, Y. Wang, and L. Liu, “Blockchain-Integrated AI Framework for Secure IoT Systems,” The Journal of Supercomputing, vol. 81, no. 3, pp. 1–25, 2025.
  • Al-Turjman, “Enhancing IoT Security through Blockchain Integration,” Frontiers in Computer Science, vol. 7, p. 123456, 2025.
  • D. Nguyen and K. Kim, “Lightweight Consensus Mechanisms in the Internet of Blockchained Things,” ACM Computing Surveys, vol. 57, no. 2, pp. 1–36, 2025.
  • Wazid et al., “Blockchain-Based Federated Machine Learning for IoT Security,” IEEE Transactions on Network Science and Engineering, vol. 11, no. 2, pp. 987–1001, 2024.
  • M. Ruzbahani, “AI-Protected Blockchain-Based IoT Environments,” arXiv preprint arXiv:2403.01234, 2024.
  • Waheed et al., “Blockchain-Enabled Collaborative Threat Intelligence using Machine Learning,” IEEE Security & Privacy, vol. 23, no. 1, pp. 44–53, 2025.
  • Buterin et al., “A Distributed Blockchain-Based Access Control for the IoT,” arXiv preprint arXiv:2501.04567, 2025.
  • Meidanet al., “Implementation of Machine Learning and Deep Learning for Securing IoT Devices,” Journal of Information Security and Applications, vol. 79, p. 103672, 2024.
  • Dwivedi et al., “Hybrid AI-Blockchain Framework for Securing Industrial IoT,” Computers & Security, vol. 141, p. 103879, 2024.
  • Zhang, J. Wu, and M. Li, “Blockchain Applications for Internet of Things: A Survey,” IEEE Communications Surveys & Tutorials, vol. 26, no. 1, pp. 456–489, 2024.
  • Kumar and A. Tripathi, “Trust Management in IoT using AI and Blockchain,” Ad Hoc Networks, vol. 151, p. 103290, 2024.
  • Salah et al., “Smart Contract-Based Distributed IoT Security,” Sensors, vol. 23, no. 7, p. 3542, 2023.
  • Tanwar et al., “Machine Learning Adoption in Blockchain-Based IoT Security,” IEEE Systems Journal, vol. 18, no. 1, pp. 902–913, 2024.
  • Ray and N. Kumar, “Privacy Preservation in IoT using AI and Blockchain,” Information Sciences, vol. 671, pp. 120–135, 2024.
  • Singh et al., “Secure Data Sharing in IoT using Blockchain and AI,” IEEE Access, vol. 12, pp. 99876–99889, 2024.
  • Conti et al., “A Survey on Security and Privacy Issues of Blockchain in IoT,” IEEE Internet of Things Journal, vol. 11, no. 2, pp. 1567–1585, 2024.
  • Wang et al., “Lightweight Blockchain for Resource-Constrained IoT Devices,” Future Internet, vol. 17, no. 1, p. 12, 2025.
  • Khan and K. R. Choo, “AI-Assisted Blockchain Architecture for Secure IoT,” Journal of Network and Computer Applications, vol. 219, p. 103712, 2025.
  • Vashistha and P. Verma, “SmartChain: AI-Driven Blockchain Framework for IoT Security,” Under Review, 2025.

M. M. Khan and M. Ali, “SmartChain: AI-driven blockchain framework for IoT security,” IPEM Journal of Computer Application & Research, vol. 10, pp. 122–133, Dec. 2025.