Secure And Privacy Preserving IoT Cybersecurity With A Blockchain Based Zero Trust Model
Keywords:
Internet of Things (IoT), Blockchain, Zero-Knowledge Proofs, Zero Trust Architecture, Post-Quantum Cryptography, Quantum-Resilient Security, Privacy-Preserving Authentication, Multi-Factor Authentication, Deep Q-Network, Access ControlAbstract
This research proposes a Unified Quantum-Resilient Blockchain–Zero-Knowledge Proof Privacy Authentication Framework (QBC-ZKPAF) designed to strengthen security, privacy, and authentication in Internet of Things (IoT) environments. The proposed framework combines blockchain technology, Zero Trust Architecture (ZTA), post-quantum cryptography, and Zero-Knowledge Proofs (ZKPs) to provide secure communication, privacy-preserving authentication, and effective access control. A hybrid Reinforcement-Lattice Blockchain Key Generation mechanism is employed to generate quantum-resistant cryptographic keys, while a Deep Q-Network Multi-Factor Secure Key (DQN-MFSK) mechanism dynamically selects secure keys based on authentication requirements and network conditions. Zero-Knowledge Proof-based signatures further protect sensitive information by enabling authentication without revealing confidential data.
The immutable blockchain ledger records device interactions, access requests, and data transactions in a tamper-resistant manner, thereby improving transparency, traceability, auditability, and post-event forensic analysis. In the event of suspicious activity or security breaches, the framework supports accurate source identification through a tracing key maintained by the audit server within the Zero Trust Architecture. By decentralizing identity management and incorporating multi-factor authentication, QBC-ZKPAF provides enhanced protection against conventional cyber threats as well as emerging quantum-based attacks. Experimental evaluation demonstrates promising performance, achieving 98% privacy preservation, 700 transactions per second (TPS), a quantum resilience score of 0.98, and 96% access control effectiveness. These results indicate that the proposed framework is a reliable and efficient solution for securing modern IoT and blockchain-based applications.
References
1. NIST, Zero Trust Architecture, Special Publication 800-207, National Institute of Standards and Technology, 2020.
2. Sannidhanam, A. H. (2025). Autonomous AI Agents for Cloud Infrastructure Operations. Journal of Contemporary Science and Technology Management, 1(01), 83–100.
3. A. K. Al Hwaitat, M. A. Almaiah, A. Ali, S. Al-Otaibi, R. Shishakly, A. Lutfi, and M. Alrawad, “Blockchain-based authentication framework for improving security in Internet of Things networks,” Electronics, vol. 12, no. 17, p. 3618, 2023.
4. Mohammed Abdul Bari, Shahanawaj Ahamad, Mohammed Rahmat Ali, “Smartphone Security and Protection Practices,” International Journal of Engineering and Applied Computer Science (IJEACS); ISBN: 9798799755577, Volume: 03, Issue: 01, December 2021 (International Journal, U.K.), Pages 1–6.
5. D. Li, Z. Yang, S. Yu, M. Duan, and S. Yang, “Micro-segmentation using VLAN and VxLAN mapping for enhanced network security,” Future Internet, vol. 16, no. 9, p. 320, 2024.
6. Sannidhanam, A. H. (2021). Real-Time Claims Processing Using Event-Driven Architectures. International Journal of Technology, Management and Humanities, 7(01), 36–50. doi:10.21590/07.01.02
7. T. H. Yuen, M. F. Esgin, J. K. Liu, M. H. Au, and Z. Ding, “DualRing: Efficient generic constructions for ring signature schemes,” in Proc. Annual International Cryptology Conference, Springer, 2021, pp. 251–281.
8. Anjani Haritha Sannidhanam. (2024). Guardrails and Safety Mechanisms for LLM-Powered Enterprise Applications. International Journal of Engineering Science & Humanities, 14(3), 273–285.
9. M. A. Uddin, A. Stranieri, I. Gondal, and V. Balasubramanian, “Blockchain adoption in IoT: A survey of challenges, applications, and possible solutions,” Blockchain: Research and Applications, vol. 2, no. 2, Art. no. 100006, 2021.
10. Ijteba Sultana, Dr. Mohd Abdul Bari, Dr. Sanjay, “Routing Performance Analysis of Infrastructure-less Wireless Networks with Intermediate Bottleneck Nodes,” International Journal of Intelligent Systems and Applications in Engineering, ISSN No.: 2147-6799, IJISAE, vol. 12, issue 3, 2024, Nov. 2023.
11. W. Alnahari and M. T. Quasim, “Privacy challenges and cyberattacks affecting IoT devices in smart city environments,” in Proc. International Congress on Advanced Technology and Engineering, 2021, pp. 1–5.
12. Anjani Haritha Sannidhanam. (2023). Zero-Downtime AI Model Updates in Real-Time Inference Systems. International Journal of Engineering Science & Humanities, 13(2), 70–78.
13. C. Bast and K.-H. Yeh, “Emerging authentication methods supporting Zero Trust security in the Internet of Things,” Symmetry, vol. 16, no. 8, p. 993, 2024.
14. Sannidhanam, A. H. (2020). Comparative Analysis of Cloud Computing Architectures for Enterprise Applications. SAMRIDDHI: A Journal of Physical Sciences, Engineering and Technology, 12(02), 169–180. doi:10.18090//samriddhi.v12i02.16
15. R. Marshal, K. Gobinath, and V. V. Rao, “Proactive cybersecurity strategies for mitigating security threats in IoT-enabled smart healthcare systems,” in Proc. IEEE Int. IoT, Electronics and Mechatronics Conf. (IEMTRONICS), 2021, pp. 1–4.
16. A. Niraula, Zero Trust Architecture for Peer-to-Peer Communication Using Blockchain and Hardware-Oriented Security, University of Toledo, Ohio, USA, 2021.
17. Distributed Data Processing Frameworks for Large-Scale Healthcare Analytics. (2019). International Journal of Advance Industrial Engineering, 7(04), 1–10. doi:10.14741/ijaie/v.7.4.01
18. Z. Ruan, “Blockchain approaches for addressing security challenges in Internet of Things systems,” in Proc. International Conference on Computer Simulation, Modeling and Information Security, 2023, pp. 572–580.
19. Anjani Haritha Sannidhanam. (2024). Prompt Engineering Patterns for Reliable LLM Outputs in Production Environments. Journal of Multidisciplinary Knowledge, 4(1), 29–39.
20. M. Luecking, C. Fries, R. Lamberti, and W. Stork, “A decentralized framework for identity and trust management in IoT environments,” in Proc. IEEE International Conference on Blockchain and Cryptocurrency, 2020, pp. 1–9.
21. Mohammed Abdul Bari, Arul Raj Natraj Rajgopal, Dr. P. Swetha, “Analysing AWS DevOps CI/CD Serverless Pipeline Lambda Function's Throughput in Relation to Other Solution,” International Journal of Intelligent Systems and Applications in Engineering, IJISAE, ISSN: 2147-6799, Nov. 2023, 12(4s), 519–526.
22. S. M. Awan, M. A. Azad, J. Arshad, U. Waheed, and T. Sharif, “A blockchain-inspired attribute-based access control approach for Zero Trust IoT systems,” Information, vol. 14, no. 2, p. 129, 2023.
23. G. Bian, R. Zhang, and B. Shao, “Identity-based privacy-preserving remote data integrity verification with a designated verifier,” IEEE Access, vol. 10, pp. 40556–40570, 2022.
24. T. Muhammad, M. T. Munir, M. Z. Munir, and M. W. Zafar, “Integrating Zero Trust and layered security mechanisms for resilient digital systems,” International Journal of Computer Science and Technology, vol. 6, no. 4, pp. 99–135, 2022.
25. R. Saxena, D. Arora, V. Nagar, and S. Mahapatra, “Bitcoin and the development of decentralized digital currency systems,” in Intelligent Systems Reference Library, Springer, 2021, pp. 13–28.
26. Sannidhanam, A. H., & Alladi, S. (2017). Cloud-Based Healthcare CRM Systems for Improved Patient Engagement. International Journal of Technology, Management and Humanities, 3(01), 32–44. doi:10.21590/ijtmh.3.03.4
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Authors
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
